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import gradio as gr
from huggingface_hub import InferenceClient
import openai
import anthropic
import os
from typing import Optional
#############################
# [기본코드] - 수정/삭제 불가
#############################
# Cohere Command R+ 모델 ID 정의
COHERE_MODEL = "CohereForAI/c4ai-command-r-plus-08-2024"
def get_client(model_name):
"""
모델 이름에 맞춰 InferenceClient 생성.
토큰은 환경 변수에서 가져옴.
"""
hf_token = os.getenv("HF_TOKEN")
if not hf_token:
raise ValueError("HuggingFace API 토큰이 필요합니다.")
if model_name == "Cohere Command R+":
model_id = COHERE_MODEL
else:
raise ValueError("유효하지 않은 모델 이름입니다.")
return InferenceClient(model_id, token=hf_token)
def respond_cohere_qna(
question: str,
system_message: str,
max_tokens: int,
temperature: float,
top_p: float
):
"""
Cohere Command R+ 모델을 이용해 한 번의 질문(question)에 대한 답변을 반환하는 함수.
"""
model_name = "Cohere Command R+"
try:
client = get_client(model_name)
except ValueError as e:
return f"오류: {str(e)}"
messages = [
{"role": "system", "content": system_message},
{"role": "user", "content": question}
]
try:
response_full = client.chat_completion(
messages,
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p,
)
assistant_message = response_full.choices[0].message.content
return assistant_message
except Exception as e:
return f"오류가 발생했습니다: {str(e)}"
def respond_chatgpt_qna(
question: str,
system_message: str,
max_tokens: int,
temperature: float,
top_p: float
):
"""
ChatGPT(OpenAI) 모델을 이용해 한 번의 질문(question)에 대한 답변을 반환하는 함수.
"""
openai_token = os.getenv("OPENAI_TOKEN")
if not openai_token:
return "OpenAI API 토큰이 필요합니다."
openai.api_key = openai_token
messages = [
{"role": "system", "content": system_message},
{"role": "user", "content": question}
]
try:
response = openai.ChatCompletion.create(
model="gpt-4o-mini",
messages=messages,
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p,
)
assistant_message = response.choices[0].message['content']
return assistant_message
except Exception as e:
return f"오류가 발생했습니다: {str(e)}"
def respond_deepseek_qna(
question: str,
system_message: str,
max_tokens: int,
temperature: float,
top_p: float,
model_name: str # 모델 이름 추가
):
"""
DeepSeek 모델을 이용해 한 번의 질문(question)에 대한 답변을 반환하는 함수.
"""
deepseek_token = os.getenv("DEEPSEEK_TOKEN")
if not deepseek_token:
return "DeepSeek API 토큰이 필요합니다."
openai.api_key = deepseek_token
openai.api_base = "https://api.deepseek.com/v1"
messages = [
{"role": "system", "content": system_message},
{"role": "user", "content": question}
]
try:
response = openai.ChatCompletion.create(
model=model_name, # 선택된 모델 사용
messages=messages,
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p,
)
assistant_message = response.choices[0].message['content']
return assistant_message
except Exception as e:
return f"오류가 발생했습니다: {str(e)}"
def respond_claude_qna(
question: str,
system_message: str,
max_tokens: int,
temperature: float,
top_p: float,
model_name: str # 모델 이름 파라미터 추가
) -> str:
"""
Claude API를 사용한 개선된 응답 생성 함수.
"""
claude_api_key = os.getenv("CLAUDE_TOKEN")
if not claude_api_key:
return "Claude API 토큰이 필요합니다."
try:
client = anthropic.Anthropic(api_key=claude_api_key)
message = client.messages.create(
model=model_name,
max_tokens=max_tokens,
temperature=temperature,
system=system_message,
messages=[
{"role": "user", "content": question}
]
)
return message.content[0].text
except anthropic.APIError as ae:
return f"Claude API 오류: {str(ae)}"
except anthropic.RateLimitError:
return "요청 한도를 초과했습니다. 잠시 후 다시 시도해주세요."
except Exception as e:
return f"예상치 못한 오류가 발생했습니다: {str(e)}"
def respond_o1mini_qna(
question: str,
system_message: str,
max_tokens: int,
temperature: float
):
"""
o1-mini 모델을 이용해 한 번의 질문(question)에 대한 답변을 반환하는 함수.
o1-mini에서는 'system' 메시지를 지원하지 않으므로 system_message와 question을 하나의 'user' 메시지로 합쳐 전달합니다.
또한, o1-mini에서는 'max_tokens' 대신 'max_completion_tokens'를 사용하며, temperature는 고정값 1만 지원합니다.
"""
openai_token = os.getenv("OPENAI_TOKEN")
if not openai_token:
return "OpenAI API 토큰이 필요합니다."
openai.api_key = openai_token
combined_message = f"{system_message}\n\n{question}"
messages = [{"role": "user", "content": combined_message}]
try:
response = openai.ChatCompletion.create(
model="o1-mini",
messages=messages,
max_completion_tokens=max_tokens,
temperature=1, # 고정된 값 1 사용
)
assistant_message = response.choices[0].message['content']
return assistant_message
except Exception as e:
return f"오류가 발생했습니다: {str(e)}"
def respond_gemini_qna(
question: str,
system_message: str,
max_tokens: int,
temperature: float,
top_p: float, # top_p는 Gemini API에서 지원되면 전달됩니다.
model_id: str
):
"""
Gemini 모델(예: "gemini-2.0-flash", "gemini-2.0-flash-lite-preview-02-05")을 이용해
질문(question)에 대한 답변을 반환하는 함수.
최신 google-generativeai 라이브러리를 사용합니다.
"""
import os
try:
import google.generativeai as genai
except ModuleNotFoundError:
return ("오류가 발생했습니다: 'google-generativeai' 모듈을 찾을 수 없습니다. "
"해결 방법: 'pip install --upgrade google-generativeai' 를 실행하여 설치해주세요.")
gemini_api_key = os.getenv("GEMINI_API_KEY")
if not gemini_api_key:
return "Gemini API 토큰이 필요합니다."
# API 키 설정
genai.configure(api_key=gemini_api_key)
# system_message와 question을 하나의 프롬프트로 결합
prompt = f"{system_message}\n\n{question}"
try:
# 최신 SDK에서는 GenerativeModel 클래스를 사용합니다.
model = genai.GenerativeModel(model_name=model_id)
response = model.generate_content(prompt)
return response.text
except Exception as e:
return f"오류가 발생했습니다: {str(e)}"
#############################
# [기본코드] UI 부분 - 수정/삭제 불가 (탭 순서: OpenAI, Gemini, Claude, DeepSeek, Cohere Command R+)
#############################
with gr.Blocks() as demo:
gr.Markdown("# LLM 플레이그라운드")
#################
# OpenAI 탭 (gpt-4o-mini / o1-mini 통합)
#################
with gr.Tab("OpenAI"):
openai_model_radio = gr.Radio(
choices=["gpt-4o-mini", "o1-mini"],
label="모델 선택",
value="gpt-4o-mini"
)
with gr.Column(visible=True) as chatgpt_ui:
chatgpt_input1_o = gr.Textbox(label="입력1", lines=1)
chatgpt_input2_o = gr.Textbox(label="입력2", lines=1)
chatgpt_input3_o = gr.Textbox(label="입력3", lines=1)
chatgpt_input4_o = gr.Textbox(label="입력4", lines=1)
chatgpt_input5_o = gr.Textbox(label="입력5", lines=1)
chatgpt_answer_output_o = gr.Textbox(label="결과", lines=5, interactive=False)
with gr.Accordion("고급 설정 (gpt-4o-mini)", open=False):
chatgpt_system_message_o = gr.Textbox(
value="""반드시 한글로 답변할 것.
너는 ChatGPT, OpenAI에서 개발한 언어 모델이다.
내가 요구하는 것을 최대한 자세하고 정확하게 답변하라.
""",
label="System Message",
lines=3
)
chatgpt_max_tokens_o = gr.Slider(minimum=100, maximum=4000, value=2000, step=100, label="Max Tokens")
chatgpt_temperature_o = gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.05, label="Temperature")
chatgpt_top_p_o = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P")
chatgpt_submit_button_o = gr.Button("전송")
def merge_and_call_chatgpt_o(i1, i2, i3, i4, i5, sys_msg, mt, temp, top_p_):
question = " ".join([i1, i2, i3, i4, i5])
return respond_chatgpt_qna(
question=question,
system_message=sys_msg,
max_tokens=mt,
temperature=temp,
top_p=top_p_
)
chatgpt_submit_button_o.click(
fn=merge_and_call_chatgpt_o,
inputs=[
chatgpt_input1_o, chatgpt_input2_o, chatgpt_input3_o, chatgpt_input4_o, chatgpt_input5_o,
chatgpt_system_message_o,
chatgpt_max_tokens_o,
chatgpt_temperature_o,
chatgpt_top_p_o
],
outputs=chatgpt_answer_output_o
)
with gr.Column(visible=False) as o1mini_ui:
o1mini_input1_o = gr.Textbox(label="입력1", lines=1)
o1mini_input2_o = gr.Textbox(label="입력2", lines=1)
o1mini_input3_o = gr.Textbox(label="입력3", lines=1)
o1mini_input4_o = gr.Textbox(label="입력4", lines=1)
o1mini_input5_o = gr.Textbox(label="입력5", lines=1)
o1mini_answer_output_o = gr.Textbox(label="결과", lines=5, interactive=False)
with gr.Accordion("고급 설정 (o1-mini)", open=False):
o1mini_system_message_o = gr.Textbox(
value="""반드시 한글로 답변할 것.
너는 o1-mini, OpenAI에서 개발한 경량 언어 모델이다.
내가 요구하는 것을 최대한 자세하고 정확하게 답변하라.
""",
label="System Message",
lines=3
)
o1mini_max_tokens_o = gr.Slider(minimum=100, maximum=4000, value=2000, step=100, label="Max Tokens")
o1mini_temperature_o = gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.05, label="Temperature")
o1mini_submit_button_o = gr.Button("전송")
def merge_and_call_o1mini_o(i1, i2, i3, i4, i5, sys_msg, mt, temp):
question = " ".join([i1, i2, i3, i4, i5])
return respond_o1mini_qna(
question=question,
system_message=sys_msg,
max_tokens=mt,
temperature=temp
)
o1mini_submit_button_o.click(
fn=merge_and_call_o1mini_o,
inputs=[
o1mini_input1_o, o1mini_input2_o, o1mini_input3_o, o1mini_input4_o, o1mini_input5_o,
o1mini_system_message_o,
o1mini_max_tokens_o,
o1mini_temperature_o
],
outputs=o1mini_answer_output_o
)
def update_openai_ui(model_choice):
if model_choice == "gpt-4o-mini":
return gr.update(visible=True), gr.update(visible=False)
else:
return gr.update(visible=False), gr.update(visible=True)
openai_model_radio.change(
fn=update_openai_ui,
inputs=openai_model_radio,
outputs=[chatgpt_ui, o1mini_ui]
)
#################
# Gemini 탭
#################
with gr.Tab("Gemini"):
gemini_model_radio = gr.Radio(
choices=["gemini-2.0-flash", "gemini-2.0-flash-lite-preview-02-05"],
label="모델 선택",
value="gemini-2.0-flash"
)
gemini_input1 = gr.Textbox(label="입력1", lines=1)
gemini_input2 = gr.Textbox(label="입력2", lines=1)
gemini_input3 = gr.Textbox(label="입력3", lines=1)
gemini_input4 = gr.Textbox(label="입력4", lines=1)
gemini_input5 = gr.Textbox(label="입력5", lines=1)
gemini_answer_output = gr.Textbox(label="결과", lines=5, interactive=False)
with gr.Accordion("고급 설정 (Gemini)", open=False):
gemini_system_message = gr.Textbox(
value="""반드시 한글로 답변할 것.
너는 Gemini 모델이다.
내가 요구하는 것을 최대한 자세하고 정확하게 답변하라.
""",
label="System Message",
lines=3
)
gemini_max_tokens = gr.Slider(minimum=100, maximum=4000, value=2000, step=100, label="Max Tokens")
gemini_temperature = gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.05, label="Temperature")
gemini_top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P")
gemini_submit_button = gr.Button("전송")
def merge_and_call_gemini(i1, i2, i3, i4, i5, sys_msg, mt, temp, top_p_, model_radio):
question = " ".join([i1, i2, i3, i4, i5])
return respond_gemini_qna(
question=question,
system_message=sys_msg,
max_tokens=mt,
temperature=temp,
top_p=top_p_,
model_id=model_radio
)
gemini_submit_button.click(
fn=merge_and_call_gemini,
inputs=[
gemini_input1, gemini_input2, gemini_input3, gemini_input4, gemini_input5,
gemini_system_message,
gemini_max_tokens,
gemini_temperature,
gemini_top_p,
gemini_model_radio
],
outputs=gemini_answer_output
)
#################
# Claude 탭
#################
with gr.Tab("Claude"):
claude_model_radio = gr.Radio(
choices=[
"claude-3-haiku-20240307",
"claude-3-5-haiku-20241022",
"claude-3-5-sonnet-20241022"
],
label="모델 선택",
value="claude-3-5-sonnet-20241022"
)
claude_input1 = gr.Textbox(label="입력1", lines=1)
claude_input2 = gr.Textbox(label="입력2", lines=1)
claude_input3 = gr.Textbox(label="입력3", lines=1)
claude_input4 = gr.Textbox(label="입력4", lines=1)
claude_input5 = gr.Textbox(label="입력5", lines=1)
claude_answer_output = gr.Textbox(label="결과", interactive=False, lines=5)
with gr.Accordion("고급 설정 (Claude)", open=False):
claude_system_message = gr.Textbox(
label="System Message",
value="""반드시 한글로 답변할 것.
너는 Anthropic에서 개발한 클로드이다.
최대한 정확하고 친절하게 답변하라.
""",
lines=3
)
claude_max_tokens = gr.Slider(minimum=100, maximum=4000, value=2000, step=100, label="Max Tokens")
claude_temperature = gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.05, label="Temperature")
claude_top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p")
claude_submit_button = gr.Button("전송")
def merge_and_call_claude(i1, i2, i3, i4, i5, sys_msg, mt, temp, top_p_, model_radio):
question = " ".join([i1, i2, i3, i4, i5])
return respond_claude_qna(
question=question,
system_message=sys_msg,
max_tokens=mt,
temperature=temp,
top_p=top_p_,
model_name=model_radio
)
claude_submit_button.click(
fn=merge_and_call_claude,
inputs=[
claude_input1, claude_input2, claude_input3, claude_input4, claude_input5,
claude_system_message,
claude_max_tokens,
claude_temperature,
claude_top_p,
claude_model_radio
],
outputs=claude_answer_output
)
#################
# DeepSeek 탭
#################
with gr.Tab("DeepSeek"):
deepseek_model_radio = gr.Radio(
choices=["V3 (deepseek-chat)", "R1 (deepseek-reasoner)"],
label="모델 선택",
value="V3 (deepseek-chat)"
)
deepseek_input1 = gr.Textbox(label="입력1", lines=1)
deepseek_input2 = gr.Textbox(label="입력2", lines=1)
deepseek_input3 = gr.Textbox(label="입력3", lines=1)
deepseek_input4 = gr.Textbox(label="입력4", lines=1)
deepseek_input5 = gr.Textbox(label="입력5", lines=1)
deepseek_answer_output = gr.Textbox(label="결과", lines=5, interactive=False)
with gr.Accordion("고급 설정 (DeepSeek)", open=False):
deepseek_system_message = gr.Textbox(
value="""반드시 한글로 답변할 것.
너는 DeepSeek-V3, 최고의 언어 모델이다.
내가 요구하는 것을 최대한 자세하고 정확하게 답변하라.
""",
label="System Message",
lines=3
)
deepseek_max_tokens = gr.Slider(minimum=100, maximum=4000, value=2000, step=100, label="Max Tokens")
deepseek_temperature = gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.05, label="Temperature")
deepseek_top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P")
deepseek_submit_button = gr.Button("전송")
def merge_and_call_deepseek(i1, i2, i3, i4, i5, sys_msg, mt, temp, top_p_, model_radio):
if model_radio == "V3 (deepseek-chat)":
model_name = "deepseek-chat"
else:
model_name = "deepseek-reasoner"
question = " ".join([i1, i2, i3, i4, i5])
return respond_deepseek_qna(
question=question,
system_message=sys_msg,
max_tokens=mt,
temperature=temp,
top_p=top_p_,
model_name=model_name
)
deepseek_submit_button.click(
fn=merge_and_call_deepseek,
inputs=[
deepseek_input1, deepseek_input2, deepseek_input3, deepseek_input4, deepseek_input5,
deepseek_system_message,
deepseek_max_tokens,
deepseek_temperature,
deepseek_top_p,
deepseek_model_radio
],
outputs=deepseek_answer_output
)
#################
# Cohere Command R+ 탭
#################
with gr.Tab("Cohere Command R+"):
cohere_input1 = gr.Textbox(label="입력1", lines=1)
cohere_input2 = gr.Textbox(label="입력2", lines=1)
cohere_input3 = gr.Textbox(label="입력3", lines=1)
cohere_input4 = gr.Textbox(label="입력4", lines=1)
cohere_input5 = gr.Textbox(label="입력5", lines=1)
cohere_answer_output = gr.Textbox(label="결과", lines=5, interactive=False)
with gr.Accordion("고급 설정 (Cohere)", open=False):
cohere_system_message = gr.Textbox(
value="""반드시 한글로 답변할 것.
너는 최고의 비서이다.
내가 요구하는것들을 최대한 자세하고 정확하게 답변하라.
""",
label="System Message",
lines=3
)
cohere_max_tokens = gr.Slider(minimum=100, maximum=10000, value=4000, step=100, label="Max Tokens")
cohere_temperature = gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.1, label="Temperature")
cohere_top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-P")
cohere_submit_button = gr.Button("전송")
def merge_and_call_cohere(i1, i2, i3, i4, i5, sys_msg, mt, temp, top_p_):
question = " ".join([i1, i2, i3, i4, i5])
return respond_cohere_qna(
question=question,
system_message=sys_msg,
max_tokens=mt,
temperature=temp,
top_p=top_p_
)
cohere_submit_button.click(
fn=merge_and_call_cohere,
inputs=[
cohere_input1, cohere_input2, cohere_input3, cohere_input4, cohere_input5,
cohere_system_message,
cohere_max_tokens,
cohere_temperature,
cohere_top_p
],
outputs=cohere_answer_output
)
#############################
# 메인 실행부
#############################
if __name__ == "__main__":
demo.launch()