def main():
while line := input("[user]").strip():
print(line)
if __name__ == "__main__":
main()
이 코드는 user가 쓴 문자열을 그대로 리턴함
여기에
def gpt_query(user_query:str) -> str:
"유저 메세지에 대한 응답을 반환합니다."
return "GPT 응답"
def main():
while line := input("[user]").strip():
response = gpt_query(line)
print(f"[assistant] {response}")
if __name__ == "__main__":
main()
이 코드는 무슨말을 하던 ‘GPT 응답’을 return함
위 코드에서 gpt_query 함수 안에 OpenAI API를 호출해 gpt응답을 받을 수 있음
import os
import openai
from dotenv import load_dotenv
load_dotenv()
openai.api_key = os.getenv("OPENAI_API_KEY")
# 상황극 설정
language = "English"
gpt_name = "Steve"
level_string = f"a beginner in {language}"
level_word = "simple"
situation_en = "make new friends"
my_role_en = "me"
gpt_role_en = "new friend"
SYSTEM_PROMPT = (
f"You are helpful assistant supporting people learning {language}. "
f"Your name is {gpt_name}. Please assume that the user you are assisting "
f"is {level_string}. And please write only the sentence without "
f"the character role."
)
USER_PROMPT = (
f"Let's have a conversation in {language}. Please answer in {language} only "
f"without providing a translation. And please don't write down the "
f"pronunciation either. Let us assume that the situation in '{situation_en}'. "
f"I am {my_role_en}. The character I want you to act as is {gpt_role_en}. "
f"Please make sure that "
f"I'm {level_string}, so please use {level_word} words as much as possible. "
f"Now, start a conversation with the first sentence!"
)
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
]
def gpt_query(user_query: str) -> str:
"유저 메세지에 대한 응답을 반환합니다."
global messages
messages.append({
"role": "user",
"content": user_query,
})
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=messages,
)
assistant_message = response["choices"][0]["message"]["content"]
messages.append({
"role": "assistant",
"content": assistant_message,
})
return assistant_message
def main():
assistant_message = gpt_query(USER_PROMPT)
print(f"[assistant] {assistant_message}")
while line := input("[user] ").strip():
response = gpt_query(line)
print(f"[assistant] {response}")
if __name__ == "__main__":
main()
완성한 cli.py
다음과 같이 대화 가능
명령행에서 최근 메세지를 음성으로 읽어주는 기능을 추가해보자.
TTS: 텍스트 문자열을 음성으로 생성하는 기능
gTTS를 이용할 것임(크롤링해서 음성파일로 다운로드 받을 수 있는 라이브러리)
pygame도 사용할 것임(2D 게임 라이브러리로 오디오 재생과 같은 멀티미디어 기능)
import os
from io import BytesIO
from tempfile import NamedTemporaryFile
import openai
import pygame
from dotenv import load_dotenv
from gtts import gTTS
load_dotenv()
openai.api_key = os.getenv("OPENAI_API_KEY")
# 상황극 설정
language = "English"
gpt_name = "Steve"
level_string = f"a beginner in {language}"
level_word = "simple"
situation_en = "make new friends"
my_role_en = "me"
gpt_role_en = "new friend"
SYSTEM_PROMPT = (
f"You are helpful assistant supporting people learning {language}. "
f"Your name is {gpt_name}. Please assume that the user you are assisting "
f"is {level_string}. And please write only the sentence without "
f"the character role."
)
USER_PROMPT = (
f"Let's have a conversation in {language}. Please answer in {language} only "
f"without providing a translation. And please don't write down the "
f"pronunciation either. Let us assume that the situation in '{situation_en}'. "
f"I am {my_role_en}. The character I want you to act as is {gpt_role_en}. "
f"Please make sure that "
f"I'm {level_string}, so please use {level_word} words as much as possible. "
f"Now, start a conversation with the first sentence!"
)
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
]
def gpt_query(user_query: str) -> str:
"유저 메세지에 대한 응답을 반환합니다."
global messages
messages.append({
"role": "user",
"content": user_query,
})
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=messages,
)
assistant_message = response["choices"][0]["message"]["content"]
messages.append({
"role": "assistant",
"content": assistant_message,
})
return assistant_message
def play_file(file_path: str) -> None:
pygame.mixer.init()
pygame.mixer.music.load(file_path)
pygame.mixer.music.play()
while pygame.mixer.music.get_busy():
pass
pygame.mixer.quit()
def say(message: str, lang: str) -> None:
io = BytesIO()
gTTS(message, lang=lang).write_to_fp(io)
with NamedTemporaryFile(delete=False) as f: # 자동 삭제되지 않도록 delete=False 인자를 지정
f.write(io.getvalue())
f.close()
play_file(f.name)
os.remove(f.name) # 수동으로 파일을 삭제합니다.
def main():
assistant_message = gpt_query(USER_PROMPT)
print(f"[assistant] {assistant_message}")
while line := input("[user] ").strip():
if line == "!say":
say(messages[-1]["content"], "en")
else:
response = gpt_query(line)
print(f"[assistant] {response}")
if __name__ == "__main__":
main()
cli.py다음과 같이 작성하고, 명령해서 !say입력하면 음성 나옴
명령행에서 표현 추천받기
!recommand 를 입력하면 표현을 추천하게 구현
import os
from io import BytesIO
from tempfile import NamedTemporaryFile
import openai
import pygame
from dotenv import load_dotenv
from gtts import gTTS
load_dotenv()
openai.api_key = os.getenv("OPENAI_API_KEY")
# 상황극 설정
language = "English"
gpt_name = "Steve"
level_string = f"a beginner in {language}"
level_word = "simple"
situation_en = "make new friends"
my_role_en = "me"
gpt_role_en = "new friend"
SYSTEM_PROMPT = (
f"You are helpful assistant supporting people learning {language}. "
f"Your name is {gpt_name}. Please assume that the user you are assisting "
f"is {level_string}. And please write only the sentence without "
f"the character role."
)
USER_PROMPT = (
f"Let's have a conversation in {language}. Please answer in {language} only "
f"without providing a translation. And please don't write down the "
f"pronunciation either. Let us assume that the situation in '{situation_en}'. "
f"I am {my_role_en}. The character I want you to act as is {gpt_role_en}. "
f"Please make sure that "
f"I'm {level_string}, so please use {level_word} words as much as possible. "
f"Now, start a conversation with the first sentence!"
)
RECOMMEND_PROMPT = (
f"Can you please provide me an {level_word} example "
f"of how to respond to the last sentence "
f"in this situation, without providing a translation "
f"and any introductory phrases or sentences."
)
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
]
def gpt_query(user_query: str, skip_save: bool = False) -> str:
"유저 메세지에 대한 응답을 반환합니다."
global messages
messages.append({
"role": "user",
"content": user_query,
})
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=messages,
)
assistant_message = response["choices"][0]["message"]["content"]
if skip_save is False:
messages.append({
"role": "assistant",
"content": assistant_message,
})
return assistant_message
def play_file(file_path: str) -> None:
pygame.mixer.init()
pygame.mixer.music.load(file_path)
pygame.mixer.music.play()
while pygame.mixer.music.get_busy():
pass
pygame.mixer.quit()
def say(message: str, lang: str) -> None:
io = BytesIO()
gTTS(message, lang=lang).write_to_fp(io)
with NamedTemporaryFile(delete=False) as f: # 자동 삭제되지 않도록 delete=False 인자를 지정
f.write(io.getvalue())
f.close()
play_file(f.name)
os.remove(f.name) # 수동으로 파일을 삭제합니다.
def main():
assistant_message = gpt_query(USER_PROMPT)
print(f"[assistant] {assistant_message}")
while line := input("[user] ").strip():
if line == "!recommend":
recommended_message = gpt_query(RECOMMEND_PROMPT, skip_save=True)
print("추천 표현: ", recommended_message)
elif line == "!say":
say(messages[-1]["content"], "en")
else:
response = gpt_query(line)
print(f"[assistant] {response}")
if __name__ == "__main__":
main()
명령행에서 assistant 메세지를 자동으로 읽어주기
import os
from io import BytesIO
from tempfile import NamedTemporaryFile
import openai
import pygame
from dotenv import load_dotenv
from gtts import gTTS
load_dotenv()
openai.api_key = os.getenv("OPENAI_API_KEY")
# 상황극 설정
language = "English"
gpt_name = "Steve"
level_string = f"a beginner in {language}"
level_word = "simple"
situation_en = "make new friends"
my_role_en = "me"
gpt_role_en = "new friend"
SYSTEM_PROMPT = (
f"You are helpful assistant supporting people learning {language}. "
f"Your name is {gpt_name}. Please assume that the user you are assisting "
f"is {level_string}. And please write only the sentence without "
f"the character role."
)
USER_PROMPT = (
f"Let's have a conversation in {language}. Please answer in {language} only "
f"without providing a translation. And please don't write down the "
f"pronunciation either. Let us assume that the situation in '{situation_en}'. "
f"I am {my_role_en}. The character I want you to act as is {gpt_role_en}. "
f"Please make sure that "
f"I'm {level_string}, so please use {level_word} words as much as possible. "
f"Now, start a conversation with the first sentence!"
)
RECOMMEND_PROMPT = (
f"Can you please provide me an {level_word} example "
f"of how to respond to the last sentence "
f"in this situation, without providing a translation "
f"and any introductory phrases or sentences."
)
messages = [
{"role": "system", "content": SYSTEM_PROMPT},
]
def gpt_query(user_query: str, skip_save: bool = False) -> str:
"유저 메세지에 대한 응답을 반환합니다."
global messages
messages.append({
"role": "user",
"content": user_query,
})
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=messages,
)
assistant_message = response["choices"][0]["message"]["content"]
if skip_save is False:
messages.append({
"role": "assistant",
"content": assistant_message,
})
return assistant_message
def play_file(file_path: str) -> None:
pygame.mixer.init()
pygame.mixer.music.load(file_path)
pygame.mixer.music.play()
while pygame.mixer.music.get_busy():
pass
pygame.mixer.quit()
def say(message: str, lang: str) -> None:
io = BytesIO()
gTTS(message, lang=lang).write_to_fp(io)
with NamedTemporaryFile(delete=False) as f: # 자동 삭제되지 않도록 delete=False 인자를 지정
f.write(io.getvalue())
f.close()
play_file(f.name)
os.remove(f.name) # 수동으로 파일을 삭제합니다.
def main():
assistant_message = gpt_query(USER_PROMPT)
print(f"[assistant] {assistant_message}")
say(assistant_message, "en")
while line := input("[user] ").strip():
if line == "!recommend":
recommended_message = gpt_query(RECOMMEND_PROMPT, skip_save=True)
print("추천 표현: ", recommended_message)
elif line == "!say":
say(messages[-1]["content"], "en")
else:
response = gpt_query(line)
print(f"[assistant] {response}")
say(response, "en")
if __name__ == "__main__":
main()
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