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import gradio as gr |
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from huggingface_hub import InferenceClient |
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import openai |
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import os |
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MODELS = { |
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"Zephyr 7B Beta": "HuggingFaceH4/zephyr-7b-beta", |
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"Meta Llama 3.1 8B": "meta-llama/Meta-Llama-3.1-8B-Instruct", |
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"Meta-Llama 3.1 70B-Instruct": "meta-llama/Meta-Llama-3.1-70B-Instruct", |
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"Microsoft": "microsoft/Phi-3-mini-4k-instruct", |
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"Mixtral 8x7B": "mistralai/Mistral-7B-Instruct-v0.3", |
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"Mixtral Nous-Hermes": "NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO", |
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"Aya-23-35B": "CohereForAI/aya-23-35B" |
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} |
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COHERE_MODEL = "CohereForAI/c4ai-command-r-plus-08-2024" |
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def get_client(model_name): |
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hf_token = os.getenv("HF_TOKEN") |
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if not hf_token: |
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raise ValueError("HF_TOKEN 환경 변수가 필요합니다.") |
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if model_name in MODELS: |
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model_id = MODELS[model_name] |
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elif model_name == "Cohere Command R+": |
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model_id = COHERE_MODEL |
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else: |
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raise ValueError("유효하지 않은 모델 이름입니다.") |
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return InferenceClient(model_id, token=hf_token) |
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def respond( |
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message, |
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chat_history, |
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model_name, |
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max_tokens, |
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temperature, |
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top_p, |
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system_message, |
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): |
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try: |
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client = get_client(model_name) |
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except ValueError as e: |
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chat_history.append((message, str(e))) |
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return chat_history |
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messages = [{"role": "system", "content": system_message}] |
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for human, assistant in chat_history: |
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messages.append({"role": "user", "content": human}) |
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messages.append({"role": "assistant", "content": assistant}) |
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messages.append({"role": "user", "content": message}) |
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try: |
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if model_name == "Cohere Command R+": |
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response = client.chat_completion( |
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messages, |
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max_tokens=max_tokens, |
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temperature=temperature, |
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top_p=top_p, |
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) |
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assistant_message = response.choices[0].message.content |
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chat_history.append((message, assistant_message)) |
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return chat_history |
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else: |
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stream = client.chat_completion( |
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messages, |
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max_tokens=max_tokens, |
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temperature=temperature, |
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top_p=top_p, |
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stream=True, |
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) |
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partial_message = "" |
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for response in stream: |
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if response.choices[0].delta.content is not None: |
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partial_message += response.choices[0].delta.content |
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if len(chat_history) > 0 and chat_history[-1][0] == message: |
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chat_history[-1] = (message, partial_message) |
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else: |
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chat_history.append((message, partial_message)) |
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yield chat_history |
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except Exception as e: |
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error_message = f"오류가 발생했습니다: {str(e)}" |
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chat_history.append((message, error_message)) |
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yield chat_history |
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def cohere_respond( |
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message, |
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chat_history, |
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system_message, |
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max_tokens, |
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temperature, |
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top_p, |
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): |
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model_name = "Cohere Command R+" |
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try: |
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client = get_client(model_name) |
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except ValueError as e: |
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chat_history.append((message, str(e))) |
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return chat_history |
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messages = [{"role": "system", "content": system_message}] |
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for human, assistant in chat_history: |
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if human: |
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messages.append({"role": "user", "content": human}) |
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if assistant: |
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messages.append({"role": "assistant", "content": assistant}) |
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messages.append({"role": "user", "content": message}) |
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response = "" |
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try: |
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response_full = client.chat_completion( |
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messages, |
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max_tokens=max_tokens, |
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temperature=temperature, |
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top_p=top_p, |
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) |
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assistant_message = response_full.choices[0].message.content |
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chat_history.append((message, assistant_message)) |
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return chat_history |
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except Exception as e: |
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error_message = f"오류가 발생했습니다: {str(e)}" |
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chat_history.append((message, error_message)) |
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return chat_history |
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def chatgpt_respond( |
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message, |
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chat_history, |
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system_message, |
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max_tokens, |
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temperature, |
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top_p, |
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): |
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openai.api_key = os.getenv("OPENAI_API_KEY") |
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if not openai.api_key: |
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chat_history.append((message, "OPENAI_API_KEY 환경 변수가 필요합니다.")) |
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return chat_history |
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messages = [{"role": "system", "content": system_message}] |
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for human, assistant in chat_history: |
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messages.append({"role": "user", "content": human}) |
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messages.append({"role": "assistant", "content": assistant}) |
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messages.append({"role": "user", "content": message}) |
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try: |
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response = openai.ChatCompletion.create( |
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model="gpt-4o-mini", |
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messages=messages, |
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max_tokens=max_tokens, |
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temperature=temperature, |
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top_p=top_p, |
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) |
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assistant_message = response.choices[0].message['content'] |
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chat_history.append((message, assistant_message)) |
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return chat_history |
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except Exception as e: |
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error_message = f"오류가 발생했습니다: {str(e)}" |
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chat_history.append((message, error_message)) |
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return chat_history |
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def clear_conversation(): |
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return [] |
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with gr.Blocks() as demo: |
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gr.Markdown("# Prompting AI Chatbot") |
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gr.Markdown("언어모델별 프롬프트 테스트 챗봇입니다.") |
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with gr.Tab("일반 모델"): |
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with gr.Row(): |
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with gr.Column(scale=1): |
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model_name = gr.Radio( |
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choices=list(MODELS.keys()), |
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label="Language Model", |
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value="Zephyr 7B Beta" |
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) |
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max_tokens = gr.Slider(minimum=0, maximum=2000, value=500, step=100, label="Max Tokens") |
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temperature = gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.05, label="Temperature") |
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top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p") |
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system_message = gr.Textbox( |
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value="""반드시 한글로 답변할 것. |
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너는 최고의 비서이다. |
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내가 요구하는것들을 최대한 자세하고 정확하게 답변하라. |
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""", |
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label="System Message", |
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lines=3 |
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) |
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with gr.Column(scale=2): |
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chatbot = gr.Chatbot() |
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msg = gr.Textbox(label="메세지를 입력하세요") |
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with gr.Row(): |
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submit_button = gr.Button("전송") |
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clear_button = gr.Button("대화 내역 지우기") |
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msg.submit(respond, [msg, chatbot, model_name, max_tokens, temperature, top_p, system_message], chatbot) |
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submit_button.click(respond, [msg, chatbot, model_name, max_tokens, temperature, top_p, system_message], chatbot) |
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clear_button.click(clear_conversation, outputs=chatbot, queue=False) |
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with gr.Tab("Cohere Command R+"): |
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with gr.Row(): |
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cohere_system_message = gr.Textbox( |
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value="""반드시 한글로 답변할 것. |
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너는 최고의 비서이다. |
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내가 요구하는것들을 최대한 자세하고 정확하게 답변하라. |
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""", |
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label="System Message", |
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lines=3 |
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) |
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cohere_max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens") |
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cohere_temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature") |
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cohere_top_p = gr.Slider( |
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minimum=0.1, |
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maximum=1.0, |
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value=0.95, |
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step=0.05, |
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label="Top-P", |
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) |
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cohere_chatbot = gr.Chatbot(height=600) |
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cohere_msg = gr.Textbox(label="메세지를 입력하세요") |
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with gr.Row(): |
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cohere_submit_button = gr.Button("전송") |
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cohere_clear_button = gr.Button("대화 내역 지우기") |
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cohere_msg.submit( |
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cohere_respond, |
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[cohere_msg, cohere_chatbot, cohere_system_message, cohere_max_tokens, cohere_temperature, cohere_top_p], |
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cohere_chatbot |
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) |
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cohere_submit_button.click( |
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cohere_respond, |
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[cohere_msg, cohere_chatbot, cohere_system_message, cohere_max_tokens, cohere_temperature, cohere_top_p], |
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cohere_chatbot |
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) |
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cohere_clear_button.click(clear_conversation, outputs=cohere_chatbot, queue=False) |
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with gr.Tab("ChatGPT"): |
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with gr.Row(): |
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chatgpt_system_message = gr.Textbox( |
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value="""반드시 한글로 답변할 것. |
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너는 ChatGPT, OpenAI에서 개발한 언어 모델이다. |
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내가 요구하는 것을 최대한 자세하고 정확하게 답변하라. |
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""", |
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label="System Message", |
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lines=3 |
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) |
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chatgpt_max_tokens = gr.Slider(minimum=1, maximum=4096, value=1024, step=1, label="Max Tokens") |
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chatgpt_temperature = gr.Slider(minimum=0.1, maximum=2.0, value=0.7, step=0.05, label="Temperature") |
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chatgpt_top_p = gr.Slider( |
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minimum=0.1, |
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maximum=1.0, |
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value=0.95, |
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step=0.05, |
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label="Top-P", |
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) |
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chatgpt_chatbot = gr.Chatbot(height=600) |
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chatgpt_msg = gr.Textbox(label="메세지를 입력하세요") |
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with gr.Row(): |
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chatgpt_submit_button = gr.Button("전송") |
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chatgpt_clear_button = gr.Button("대화 내역 지우기") |
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chatgpt_msg.submit( |
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chatgpt_respond, |
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[chatgpt_msg, chatgpt_chatbot, chatgpt_system_message, chatgpt_max_tokens, chatgpt_temperature, chatgpt_top_p], |
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chatgpt_chatbot |
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) |
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chatgpt_submit_button.click( |
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chatgpt_respond, |
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[chatgpt_msg, chatgpt_chatbot, chatgpt_system_message, chatgpt_max_tokens, chatgpt_temperature, chatgpt_top_p], |
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chatgpt_chatbot |
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) |
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chatgpt_clear_button.click(clear_conversation, outputs=chatgpt_chatbot, queue=False) |
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if __name__ == "__main__": |
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demo.launch() |
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