import gradio as gr import openai import requests import csv prompt_templates = {"Por defecto": "Comportate como un asistente de escritura."} def get_empty_state(): return {"total_tokens": 0, "messages": []} def download_prompt_templates(): url = "https://raw.githubusercontent.com/ioseobcn/prompt-base/main/prompt-base-v3" try: response = requests.get(url) reader = csv.reader(response.text.splitlines()) next(reader) # skip the header row for row in reader: if len(row) >= 2: act = row[0].strip('"') prompt = row[1].strip('"') prompt_templates[act] = prompt except requests.exceptions.RequestException as e: print(f"An error occurred while downloading prompt templates: {e}") return choices = list(prompt_templates.keys()) choices = choices[:1] + sorted(choices[1:]) return gr.update(value=choices[0], choices=choices) def on_token_change(user_token): openai.api_key = user_token def on_prompt_template_change(prompt_template): if not isinstance(prompt_template, str): return return prompt_templates[prompt_template] def submit_message(user_token, prompt, prompt_template, temperature, max_tokens, context_length, state): history = state['messages'] if not prompt: return gr.update(value=''), [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], f"Total tokens used: {state['total_tokens']}", state prompt_template = prompt_templates[prompt_template] system_prompt = [] if prompt_template: system_prompt = [{ "role": "system", "content": prompt_template }] prompt_msg = { "role": "user", "content": prompt } if not user_token: history.append(prompt_msg) history.append({ "role": "system", "content": "Error: OpenAI API Key is not set." }) return '', [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], f"Total tokens used: 0", state try: completion = openai.ChatCompletion.create(model="gpt-4", messages=system_prompt + history[-context_length*2:] + [prompt_msg], temperature=temperature, max_tokens=max_tokens) history.append(prompt_msg) history.append(completion.choices[0].message.to_dict()) state['total_tokens'] += completion['usage']['total_tokens'] except Exception as e: history.append(prompt_msg) history.append({ "role": "system", "content": f"Error: {e}" }) total_tokens_used_msg = f"Total tokens used: {state['total_tokens']}" chat_messages = [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)] return '', chat_messages, total_tokens_used_msg, state def clear_conversation(): return gr.update(value=None, visible=True), None, "", get_empty_state() css = """ #col-container {max-width: 80%; margin-left: auto; margin-right: auto;} #chatbox {min-height: 400px;} #header {text-align: center;} #prompt_template_preview {padding: 1em; border-width: 1px; border-style: solid; border-color: #e0e0e0; border-radius: 4px;} #total_tokens_str {text-align: right; font-size: 0.8em; color: #666;} #label {font-size: 0.8em; padding: 0.5em; margin: 0;} .message { font-size: 1.2em; } """ with gr.Blocks(css=css) as demo: state = gr.State(get_empty_state()) with gr.Column(elem_id="col-container"): gr.Markdown("""## GPT4 Demo en Español Utilizando la API oficial (modelo gpt-4) Adaptación de [OpenAI ChatGPT Demo](https://huggingface.co/spaces/anzorq/chatgpt-demo) al español y a API GPT4. Plantillas de Prompts traducidas de [awesome-chatgpt-prompts](https://github.com/f/awesome-chatgpt-prompts) Adaptado por [InnovaOrigen](https://innovaorigen.io)""", elem_id="header") with gr.Row(): with gr.Column(): chatbot = gr.Chatbot(elem_id="chatbox") input_message = gr.Textbox(show_label=False, placeholder="Introduce el texto y pulsa intro", visible=True).style(container=False) btn_submit = gr.Button("Enviar") total_tokens_str = gr.Markdown(elem_id="total_tokens_str") btn_clear_conversation = gr.Button("🔃 Iniciar una nueva conversación") with gr.Column(): gr.Markdown("Introduce tu clave API de OpenAI. Puedes obtener una [aquí](https://platform.openai.com/account/api-keys).", elem_id="label") user_token = gr.Textbox(value='', placeholder="Clave API OpenAI", type="password", show_label=False) prompt_template = gr.Dropdown(label="Establece una instrucción personalizada para el chatbot:", choices=list(prompt_templates.keys())) prompt_template_preview = gr.Markdown(elem_id="prompt_template_preview") with gr.Accordion("Parámetros avanzados", open=False): temperature = gr.Slider(minimum=0, maximum=2.0, value=0.7, step=0.1, label="Temperatura", info="Más alto = más creativo/caótico") max_tokens = gr.Slider(minimum=100, maximum=4096, value=1000, step=1, label="Número máximo de fichas por respuesta") context_length = gr.Slider(minimum=1, maximum=50, value=10, step=1, label="Longitud del contexto", info="Número de mensajes previos a enviar al chatbot. Ten cuidado con los valores altos, ya que pueden inflar el presupuesto de tokens rápidamente.") btn_submit.click(submit_message, [user_token, input_message, prompt_template, temperature, max_tokens, context_length, state], [input_message, chatbot, total_tokens_str, state]) input_message.submit(submit_message, [user_token, input_message, prompt_template, temperature, max_tokens, context_length, state], [input_message, chatbot, total_tokens_str, state]) btn_clear_conversation.click(clear_conversation, [], [input_message, chatbot, total_tokens_str, state]) prompt_template.change(on_prompt_template_change, inputs=[prompt_template], outputs=[prompt_template_preview]) user_token.change(on_token_change, inputs=[user_token], outputs=[]) demo.load(download_prompt_templates, inputs=None, outputs=[prompt_template], queur=False) demo.queue(concurrency_count=10) demo.launch(height='800px')