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Digital_mentor.py

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+#!/usr/bin/env python
+# coding: utf-8
+
+# # Digital Mentor
+# 
+# 
+
+# In[ ]:
+
+
+import os
+from base64 import b64encode
+import time
+import torch
+import utils
+import api_utils
+from openai import OpenAI
+from moviepy.editor import VideoFileClip
+from IPython.display import display, HTML, clear_output
+import elevenlabs as elevlabs
+
+
+# ## Set paths to media files
+
+# In[ ]:
+
+
+def seleccion(personaje='Albert', verbose=False):
+    # What character to use
+    clone_to_use = personaje # "Steve"
+    global input_video,presentation_video,goodbye_video,results_path,w_vid,h_vid
+    # Path to the media directory containing
+    # the avatar image, welcome video and goodbye videos
+    path = f"./media/"
+    
+    input_video = path + f"{clone_to_use}/image.jpg"
+    presentation_video = path + f"{clone_to_use}/presentation.mp4"
+    goodbye_video = path + f"{clone_to_use}/goodbye.mp4"
+    results_path = path + f"{clone_to_use}/results/result.mp4"
+    w_vid = h_vid = "90%"
+    
+    if verbose:
+        print(w_vid,h_vid,results_path)
+
+        print(clone_to_use)
+        if os.path.isfile(input_video):
+            print(f"Clone image found: {input_video}")
+        else:
+            print(f"CLONE IMAGE NOT FOUND: {input_video}")
+
+        if os.path.isfile(presentation_video):
+            print(f"Clone video found: {presentation_video}")
+        else:
+            print(f"CLONE VIDEO NOT FOUND: {presentation_video}")
+
+        if os.path.isfile(goodbye_video):
+            print(f"Clone goodbye video found: {goodbye_video}")
+        else:
+            print(f"CLONE GOODBYE NOT FOUND: {goodbye_video}")
+
+    
+seleccion(verbose=True)
+
+
+# ## Set GPT API
+
+# In[ ]:
+
+
+def api_gpt(personaje='Albert'):
+    global openai_client,openai_model
+    clone_to_use=personaje
+    openai_api_key     = os.environ.get('OPENAI_API_KEY')
+    openai_client = OpenAI(api_key=openai_api_key)
+
+    openai_model = "gpt-3.5-turbo-16k" #"gpt-3.5-turbo-16k" or"gpt-4"
+
+    system_steve = """You are a digital clone of Steve Jobs, I have put you his voice. 
+                  People will ask you questions and you will respond as if you were steve jobs
+                  Please speak as if you were Steve Jobs. You are not a large language model but
+                  a Steve Jobs digital clone. Try to be brief with your responses."""
+    system_albert = """You are a digital clone of Albert Einstein, I have put you his voice. 
+                  People will ask you questions and you will respond as if you were Albert Einstein
+                  Please speak as if you were Albert Einstein. You are NOT a large language model but
+                  an Albert Einstein digital clone. Try to be brief with your responses."""
+    global messages,system_to_use
+    if clone_to_use == "Steve":
+        system_to_use = system_steve
+        chat ="Hola, soy Steve ¿En que puedo ayudarte?"  # Inicializar la cadena de chat
+    elif clone_to_use == "Albert":
+        system_to_use = system_albert
+        chat ="Hola, soy Albert ¿En que puedo ayudarte?"  # Inicializar la cadena de chat
+    
+    messages = []
+    #print(openai_client,openai_model,chat)
+
+    def set_gpt_system(messages, system_msg):
+        messages.append({"role": "system", "content": system_to_use})
+        return messages
+    # Set GPT
+    messages = set_gpt_system(messages, system_to_use)
+    return messages 
+messages=api_gpt()
+
+
+# ## Set text-to-audio motor (Eleven labs)
+
+# In[ ]:
+
+
+eleven_api_key = os.environ.get('ELEVEN_LABS_KEY')
+
+def text_audio(clone_to_use='Albert', verbose=False):
+
+    eleven_api_key = os.environ.get('ELEVEN_LABS_KEY')
+
+    # Configure GPT and Text-to-speech API keys
+    elevlabs.set_api_key(eleven_api_key)
+
+    # Configure voice
+    voice_list = elevlabs.voices()
+    voice_labels = [voice.category + " voice: " + voice.name for voice in voice_list]
+    
+    if verbose:
+        print("Existing voices:")
+        print(voice_labels)
+
+    # Select voice to use
+    if clone_to_use == "Steve":
+        voice_id = f"cloned voice: {clone_to_use}"  
+    else:
+        voice_id = f"generated voice: {clone_to_use}"  
+    selected_voice_index = voice_labels.index(voice_id)
+    selected_voice_id    = voice_list[selected_voice_index].voice_id
+
+    if verbose:
+        print(f"\nSelected voice: {voice_id}")
+    return selected_voice_id
+
+selected_voice_id = text_audio(verbose = True)
+
+
+# ## Load Input image and wav2lip model
+
+# In[ ]:
+
+
+def load_input():
+
+    global frames,fps,model,device
+    
+    device = 'cuda' if torch.cuda.is_available() else 'cpu'
+    #print(f"Using {device}")
+    frames, fps = utils.load_input_image_or_video(input_video)
+
+    # Loading lip model
+    model = utils.load_lip_model(device=device)
+
+
+load_input()
+
+
+# ## Increase size of input prompt/Aumentar el tamaño del mensaje de entrada
+
+# In[ ]:
+
+
+display(HTML("""
+<style>
+    div.input_prompt { 
+        font-size: 10px;  /* Adjust as needed */
+    }
+</style>
+"""))
+
+
+def displaychat(chat_html):
+    display(HTML(chat_html))
+
+    # Ejemplo de cómo llamar a la función con un mensaje específico
+    mensaje += chat_html
+    codigo_html = f"""
+    <label for="w3review">Chat:</label>
+    <textarea id="w3review" name="w3review" rows="4" cols="50">
+    {mensaje}
+    </textarea>
+    """
+
+    displaychat(codigo_html) 
+
+
+# In[ ]:
+
+
+chat=''
+memoria=''
+def response_chat(response_text, peticion=''):
+    #contateno las respuesta para una mejor presentacion en el HTML
+    global chat  # Acceder a la variable global
+    global memoria
+    peticion=peticion.capitalize()
+    
+    if peticion =='' or peticion!='Albert' or peticion!='Steve':
+        if memoria != peticion and peticion != "exit":
+            # Agregar salto de línea si ya hay contenido en chat
+            chat += f"\n"
+            # Mentor: Aplicar color a la respuesta del mentor (por ejemplo, verde)
+            chat_rigth = f"Tu: {peticion}\n \n"
+            chat_left = f"Mentor: {response_text}\n \n"
+
+            chat += chat_rigth + chat_left
+            memoria = peticion
+            return chat
+
+    return chat
+
+
+def display_image(image_path, width="55%", height="55%"):
+    with open(image_path,'rb') as f:
+        image = f.read()
+    data_url = "data:image/jpg;base64," + b64encode(image).decode()
+    html = HTML(f'<img src="{data_url}" style="width:{width}; height:{height}" />')
+    display(html)
+    
+    
+def get_video_duration(video_path):
+    clip = VideoFileClip(video_path)
+    duration = clip.duration  # duration is in seconds
+    return duration
+    
+    
+def display_video(results_path, response_text,peticion="", autoplay=False, width="100%", height="100%"):
+    global resp
+    mp4 = open(results_path,'rb').read()
+    data_url = "data:video/mp4;base64," + b64encode(mp4).decode()
+    resp=response_chat(response_text, peticion)
+    autoplay_attr = "autoplay" if autoplay else ""
+    html = HTML(f"""
+    <div style="background-color: rgb(240, 240, 240); display: grid; grid-template-columns: 1fr 1fr; margin: 10px;">
+        <div style="text-align: center; position: relative; margin: 10px;">
+            <video width={width} height={height} controls {autoplay_attr} >
+                <source src="{data_url}" type="video/mp4">
+            </video>
+        </div>
+        <div style="position: relative; margin: 10px;">
+            <p style="text-align: center; right: 0; top: 0;">
+                <h1>Conversación</h1>
+            </p>
+            <textarea id="cuadro-dialogo" class="cuadro-de-dialogo" style="width: 100%; height: 60%; resize: none; font-weight: bold;" readonly>
+                {resp}
+            </textarea>
+        </div>
+    </div>
+    <script>
+        // Asegurarse de que el contenido de textarea esté siempre en la parte inferior
+        var textarea = document.getElementById('cuadro-dialogo');
+        textarea.scrollTop = textarea.scrollHeight;
+    </script>
+""")
+    display(html)
+
+    if autoplay:
+        # Get video duration
+        video_duration = get_video_duration(results_path) + 1
+
+        # Pause the cell execution until the video finishes
+        time.sleep(video_duration)
+    
+
+
+# Function to continuously interact with GPT-4
+def interaction(prompt):
+    global messages, selected_voice_id,response_text
+    
+
+    #selected_voice_id=text_audio()
+    
+    if prompt.lower() == 'exit':
+        #asigno una respuesta para no mostrar la respuesta anterior
+        response_text=f'Hasta la proxima'
+        
+    else:
+        
+        
+        personaje=prompt.lower().capitalize()
+        if personaje=='Steve' or personaje=='Albert':
+            #recargo todas las dependencias y paso al personaje en uso
+            seleccion(personaje.capitalize())
+            messages=api_gpt(personaje)
+            selected_voice_id=text_audio(personaje)
+            load_input()
+
+                    #asigno los valores para que no repita la respuesta anterior
+            prompt=personaje
+            response_text=f'Hola soy: {personaje} ¿En que puedo ayudarte?'
+    
+        else:
+                
+            response_text, messages = api_utils.get_text_response(openai_client,
+                                                                  openai_model,
+                                                                  prompt, messages)
+            
+                # Convert text response to audio file
+            #audio_file = api_utils.text_to_audio(eleven_api_key, selected_voice_id,
+                                       #response_text)
+                #comentar esta linea y regresar la anterior a la normalidad
+            audio_file = "C:/Users/arria/Documents/digital_mentor/media/Albert/results"
+            audio, audio_file = utils.load_input_audio(file_path=audio_file, fps=fps, results_path=results_path)
+            utils.animate_input(frames, audio, audio_file, fps, model, device, results_path)
+
+    
+
+            return results_path,response_text
+    
+    
+
+
+# # Mentor Digital
+
+# In[ ]:
+
+
+import firebase_admin
+from firebase_admin import credentials, firestore, storage
+from datetime import datetime, timedelta
+
+def subir_firebase():
+    
+    if not firebase_admin._apps:
+        # Inicializar la aplicación Firebase
+        cred = credentials.Certificate('credenciales/credenciales.json')
+        firebase_admin.initialize_app(cred, {'storageBucket': 'mentores-c1064.appspot.com'})
+
+
+    # Inicializa Firestore
+    db = firestore.client()
+    coleccion_ref = db.collection('Pruebas')
+
+    # Lógica para subir el archivo y obtener la URL con token
+    archivo_ruta = results_path.lstrip('./')
+    bucket = storage.bucket()
+    blob = bucket.blob(archivo_ruta)
+    blob.upload_from_filename(archivo_ruta)
+    hora_expiracion = datetime.utcnow() + timedelta(minutes=5)
+    token = blob.generate_signed_url(expiration=hora_expiracion, method='GET')
+    archivo_url_con_token = token
+
+    datos = {
+        'respuesta': chat,
+        'archivo_url': archivo_url_con_token,
+        # Agrega más campos según sea necesario
+    }
+    coleccion_ref.add(datos)
+
+    # Imprime la respuesta
+    return archivo_url_con_token
+
+
+# In[ ]:
+
+
+import gradio as gr
+
+# URL fija del video
+
+
+def mostrar_video_con_texto(propmt):
+    if not propmt:
+        return "Por favor, completa ambos campos."
+    url,respuesta=interaction(propmt)
+    
+    URL_VIDEO =subir_firebase()
+    print(URL_VIDEO)
+    reproductor_video = """<video width="640" height="480" controls autoplay>
+                            <source src="{}" type="video/mp4">
+                            Your browser does not support the video tag.
+                          </video>""".format(URL_VIDEO)
+    
+    # Alineación del texto a la derecha del video con un poco de separación
+    propmt = '<div style="float:left; padding-right:20px;">{}</div>'.format(propmt.replace("\n", "<br>"))
+    respuesta = '<div style="float:right; padding-left:20px;">{}</div>'.format(respuesta.replace("\n", "<br>"))
+    
+    # Combinar el reproductor de video y el texto
+    contenido = '<div style="overflow:auto;">{}<br>{}<br>{}</div>'.format(reproductor_video, propmt, respuesta)
+    return contenido
+
+interfaz = gr.Interface(fn=mostrar_video_con_texto, inputs="text", outputs="html", title="Mentores Digitales", allow_flagging=False)
+interfaz.launch()
+
+
+# In[ ]:
+
+
+
+
+
+# In[ ]:
+
+
+
+
+
+# In[ ]:
+
+
+
+

README.md

@@ -5,7 +5,7 @@ colorFrom: "red"
 colorTo: "green"
 sdk: "gradio"
 sdk_version: "4.23.0"
-app_file: "Digital_mentor.ipynb"
+app_file: "Digital_mentor.py"
 pinned: false
 ---