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# -*- coding: utf-8 -*-
"""Untitled1.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1yIRyQq7IUIqBQiXAPKoa0n2gT8Lr_qMw
"""

#!pip install openai
#!pip install imageio
#!pip install replicate
#!pip install gradio

"""## Importing Libraries"""

import openai
import re
import pandas as pd
import replicate
import pandas as pd
from PIL import Image
import requests
from io import BytesIO
import os
from IPython.display import Audio, display
import gradio as gr
import numpy
from PIL import ImageDraw
from PIL import ImageFont
import random

#!git clone https://github.com/Neelanjan-chakraborty/MelodyGen.git

#!ls MelodyGen

"""## Function To Generate Genre Based on Mood"""

def generate_genre_recommendations(mood,key):
    openai.api_key=key
    response = openai.Completion.create(
        engine='text-davinci-003',
        prompt=f"I'm feeling {mood} and I want only genre recommendations and not songs also please separate using comma.",
        max_tokens=100,
        n=1,
        stop=None,
        temperature=0.5
    )

    genres = set(response.choices[0].text.strip().split(','))  # Extract genres from response

    #if len(genres) < 3:
    #    # Provide some default genre recommendations
    #    genres = {'Pop', 'Rock', 'Electronic'}

    genre_recommendations = list(genres)[:3]  # Limit to 3 unique genres

    return ', '.join(genre_recommendations)  # Return as comma-separated string

def recommend(user_mood,key):
  genre_recommendations = generate_genre_recommendations(user_mood,key)
  out = genre_recommendations.split(',')
  return out

"""## Function to Generate Melody"""

def melodygen(api_token,prompt):
  client = replicate.Client(api_token)
  output = client.run(
      "joehoover/musicgen:ba9bdc5a86f60525ba23590a03ae1e407b9a40f4a318a85af85748d641e6659f",
      input={"model_version": "melody","prompt":prompt,"continuation_start": 0,"continuation_end": 30, "duration":30,
      }
  )
  return output

#api_token='r8_Z30IhmLhqMoeJeNkl4S92JzSp8stlh82NZAnI'
#prompt=input("Enter your Genre : ")
#melodygen(api_token,prompt)

"""## Function To Generate a Song Name"""

def generate_song_name(mood,key):
  openai.api_key=key
  response = openai.Completion.create(
      engine='text-davinci-003',
      prompt=f"I'm feeling {mood} and I want only random ai generated Song Name and please separate these names using comma.",
      max_tokens=100,
      n=1,
      stop=None,
      temperature=0.5
  )

  names = set(response.choices[0].text.strip().split(','))  # Extract genres from response
  get_names = list(names)[:3]  # Limit to 3 unique genres
  return ', '.join(get_names)  # Return as comma-separated string(mood):

"""## Function To Generate Album Art and Album Art Animation"""

def albumart(user_mood,key,name):
  openai.api_key=key
  response = openai.Image.create(
    prompt=f"Music album art of mood{user_mood}",
    n=1,
    size="512x512"
  )
  image_url = response['data'][0]['url']
  # Fetch the image from the URL
  response = requests.get(image_url)
  response.raise_for_status()
  # Load the image into a PIL Image object
  image = Image.open(BytesIO(response.content))
  # Load the font
  font_path = "MelodyGen/Lobster-Regular.ttf"
  font_size = 48
  font = ImageFont.truetype(font_path, font_size)
  position = (image.width // 2, image.height // 2)
  # Create a new ImageDraw object
  draw = ImageDraw.Draw(image)
  # Get a random color
  color = (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
  # Calculate the position to center the text
  text_width, text_height = draw.textsize(name, font=font)
  text_position = (position[0] - text_width // 2, position[1] - text_height // 2)
  # Add the text to the image
  draw.text(text_position, name, font=font, fill=color)
  path='album_art.jpg'
  image.save(path)
  return path



#overlay_images(background_image_path, foreground_image_path)

from PIL import Image, ImageSequence
def overlay_images(background_image_path):
    foreground_image_path='MelodyGen/Mockup4.png'
    num_frames=36
    rotation_angle=10
    # Open the background and foreground images
    background_image = Image.open(background_image_path).resize((600, 600))
    foreground_image = Image.open(foreground_image_path).resize((1024, 768)).convert("RGBA")

    # Create a new image with transparency
    final_image = Image.new("RGBA", (1024, 768))

    # Calculate the position to paste the background image at the center
    paste_x = int(100.50)
    paste_y = int(100.50)

    # Create a list to store the frames of the GIF animation
    frames = []

    # Calculate the center point of the background image
    center_x = int(background_image.width / 2)
    center_y = int(background_image.height / 2)

    # Rotate the background image and create frames for the GIF animation
    for angle in range(0, 360, rotation_angle):
        # Create a copy of the background image
        rotated_image = background_image.copy()

        # Rotate the image by the specified angle around its center
        rotated_image = rotated_image.rotate(angle, resample=Image.BICUBIC, center=(center_x, center_y))

        # Overlay the rotated background image at the center of the final image
        final_image.paste(rotated_image, (paste_x, paste_y))

        # Overlay the foreground image on the background image
        final_image.paste(foreground_image, (0, 0), mask=foreground_image)

        # Append the current frame to the list of frames
        frames.append(final_image.copy())

    # Convert the image mode of frames to RGB (removing alpha channel)
    frames_rgb = [frame.convert("RGB") for frame in frames]

    # Save the frames as an animated GIF
    output_path = "animation2.gif"
    frames_rgb[0].save(output_path, save_all=True, append_images=frames_rgb[1:], loop=0, duration=100,optimize=True, quality=100)

    # Return the output path of the animated GIF
    return output_path




#background_image_path = "/content/input.png"  # Path to the background image
#foreground_image_path = "/content/Mockup4.png"  # Path to the foreground PNG image
#rotation_angle = 10

#overlay_images(background_image_path, foreground_image_path)

def main_func(user_mood,key,api_token,genre):
  if genre is None:
      out = recommend(user_mood, key)[0]
  else:
      out = genre
  name=generate_song_name(user_mood,key).split(",")
  image=albumart(user_mood ,key,name[0])
  album_art=overlay_images(image)
  song=melodygen(api_token,out[0])

  return album_art,name[0],genre,song


"""## Gradio UI"""

css1= """.gradio-container{
	background: linear-gradient(-45deg, #ee7752, #e73c7e, #23a6d5, #23d5ab);
	background-size: 400% 400%;
	animation: gradient 15s ease infinite;
	height: 100vh;
}

@keyframes gradient {
	0% {
		background-position: 0% 50%;
	}
	50% {
		background-position: 100% 50%;
	}
	100% {
		background-position: 0% 50%;
	}
}
.mood {
background: linear-gradient(-45deg, #ee7752, #e73c7e, #23a6d5, #23d5ab);
	background-size: 400% 400%;
	animation: gradient 15s ease infinite;
	height: 100vh;
}

@keyframes gradient {
	0% {
		background-position: 0% 50%;
	}
	50% {
		background-position: 100% 50%;
	}
	100% {
		background-position: 0% 50%;
	}
}
.OpenAI {
background: linear-gradient(-45deg, #ee7752, #e73c7e, #23a6d5, #23d5ab)!important;
	animation: gradient 15s ease infinite!important;
}

@keyframes gradient {
	0% {
		background-position: 0% 50%;
	}
	50% {
		background-position: 100% 50%;
	}
	100% {
		background-position: 0% 50%;
	}
}
}
"""

def check_box(check,ch):
  if(check==True):
      return gr.Dropdown.update(visible=True)
  return gr.Dropdown.update(visible=False, value=None)


with gr.Blocks(css=css1,theme='freddyaboulton/dracula_revamped',title="🎵MoodMelody🤖 by Neelanjan",thumbnail="MelodyGen/Mood-Melody.jpg") as demo:
  with gr.Row():
    with gr.Column(scale=1):
      Mood=textbox = gr.Textbox(label="Enter Your Mood",value="Happy",placeholder="How is Your Mood Now?", elem_id="warning", elem_classes="feedback")
      Key=textbox = gr.Textbox(label="Enter Open AI Key",placeholder="sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",elem_id="warning", elem_classes="feedback")
      Key2=textbox = gr.Textbox(label="Enter Replicate Key",placeholder="r8-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",elem_id="warning", elem_classes="feedback")
      check=gr.Checkbox(label="Custom Genre?", info="Select if you want custom Genres",value=True,elem_id="warning", elem_classes="feedback")
      ch=gr.Dropdown(
          [
              "Acoustic","Alternative","Ambient","Blues","Classical","Country","Dance","Disco","Electronic","Folk","Funk","Gospel","Hip Hop","Indie","Jazz","Latin","Metal","Opera","Pop","Punk",
              "R&B","Reggae","Rock","Soul","Techno","World",# Add more genres as needed
          ],max_choices=1,
          multiselect=True,visible=True,
          label="Music Genres",
          info="Select  only one  genre of music"
      )

      check.change(check_box, check, ch)
      btn = gr.Button(value="Generate Song")
    with gr.Column(scale=4):
      SongName=gr.Textbox(label="Song Name",placeholder="Song Name will appear Here")
      Genres=gr.Textbox(label="Genre",placeholder="Genres")
      AlbumArt=gr.Image(label="AI Generated Album Art")
      MusicGen=gr.Audio(label="AI Generated Music",format="wav")



    btn.click(main_func, inputs=[Mood,Key,Key2,ch], outputs=[AlbumArt,SongName,Genres,MusicGen])

if __name__ == "__main__":
   demo.launch(show_error=True,debug=True)