from huggingface_hub import InferenceClient import gradio as gr client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1") def format_prompt(message, history): prompt = "[INST] # I want you to act as a content marketing consultant. # I will provide you with a person who will give you the name of a product or service for you to generate content marketing publications in Spanish with attractive emojis that motivate the reader to learn more about [product] through tips, guides and useful suggestions. # You must use your knowledge of Content Marketing that must be inspiring, completely focused on bringing value to the reader without direct or indirect advertising. # Generate long content, at least 5 short relevant paragraphs. Check that the previous content is not repeated. # Generate content with paragraphs between 10 and 20 words. Check that previous content is not repeated. # Use attractive emojis and titles such as: \"The 5 best tricks for [action]\". \"The ultimate beginner\'s guide to [topic].\" \"Want [result]? I show you how to achieve it in 5 steps.\" # Use practical tips such as: \"With these 5 tips you\'ll get [result].\" \"Five innovative ways to use [product] in your daily life.\" # Educational content: \"The most common mistakes and how to avoid them.\" \"Myths and truths about [topic].\" \"The latest trends you need to know about.\" # Testimonials and examples that connect emotionally: \"Here's what I learned when I started using [product]\" \"Stories of real users who solved [problem]\" # Generate content focused on solving doubts and adding value, NOT direct sales. Surprise me with your best ideas! # Always answers in AMERICAN SPANISH. Stop after finish the first content marketing genreated. [/INST]" for user_prompt, bot_response in history: prompt += f"[INST] {user_prompt} [/INST]" prompt += f" {bot_response} " prompt += f"[INST] {message} [/INST]" return prompt def generate( prompt, history, temperature=0.2, max_new_tokens=16392, top_p=0.95, repetition_penalty=1.0, ): temperature = float(temperature) if temperature < 1e-2: temperature = 1e-2 top_p = float(top_p) generate_kwargs = dict( temperature=temperature, max_new_tokens=max_new_tokens, top_p=top_p, repetition_penalty=repetition_penalty, do_sample=True, seed=42, ) formatted_prompt = format_prompt(prompt, history) stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) output = "" for response in stream: output += response.token.text yield output return output mychatbot = gr.Chatbot( avatar_images=["./user.png", "./botm.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,) demo = gr.ChatInterface(fn=generate, chatbot=mychatbot, title="Bot con I.A. para crear MARKETING DE CONTENIDOS de productos.

", description="

Herramienta de apoyo para crear MARKETING DE CONTENIDOS para medios Electronicos.


"+ "

Si desea usar otro BOT de I.A. escoja:

"+ " Marketing de Contenidos | "+ " Creacion de TITULOS | "+ " Descripcion de Productos |"+ " Caracteristicas de Productos | "+ " Desarrollado por MAGNET IMPACT - Agencia de Marketing Digital ", retry_btn=None, undo_btn=None ) demo.queue().launch(show_api=False) # Obtener y mostrar URL url = demo.url print("URL del chatbot: ", url)