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# import gradio as gr
# import os
# from acrcloud.recognizer import ACRCloudRecognizer
# import tempfile
# import shutil
# import json
# # Retrieve ACRCloud credentials from environment variables
# acr_access_key = os.environ.get('ACR_ACCESS_KEY')
# acr_access_secret = os.environ.get('ACR_ACCESS_SECRET')
# acr_host = 'identify-ap-southeast-1.acrcloud.com' # os.environ.get('ACR_HOST', 'eu-west-1.api.acrcloud.com')
# # ACRCloud recognizer configuration
# config = {
# 'host': acr_host,
# 'access_key': acr_access_key,
# 'access_secret': acr_access_secret,
# 'timeout': 10 # seconds
# }
# # Initialize ACRCloud recognizer
# acr = ACRCloudRecognizer(config)
# def identify_audio(file):
# # Gradio provides a file object, and file.name contains the path
# file_path = file.name # Gradio file object already provides a file path
# # Get the duration of the audio file in milliseconds
# duration_ms = int(acr.get_duration_ms_by_file(file_path))
# results = []
# # Full recognition result
# full_result = acr.recognize_by_file(file_path, 0)
# full_result_dict = json.loads(full_result)
# music = full_result_dict['metadata']['music'][0]
# # Spotify link
# spotify_track_id = music['external_metadata']['spotify']['track']['id']
# spotify_link = f"https://open.spotify.com/track/{spotify_track_id}"
# # Deezer link
# deezer_track_id = music['external_metadata']['deezer']['track']['id']
# deezer_link = f"https://www.deezer.com/track/{deezer_track_id}"
# # Final markdown result
# result_md = f"""
# ### **Full Result**:
# - **Track**: {music['title']}
# - **Artist**: {music['artists'][0]['name']}
# - **Album**: {music['album']['name']}
# - **Release Date**: {music['release_date']}
# - **Score**: {music['score']}%
# - **Download Link**:
# - [Listen on Spotify]({spotify_link})
# - [Listen on Deezer]({deezer_link})
# """
# return gr.Markdown(result_md)
# # Create Gradio interface
# iface = gr.Interface(
# fn=identify_audio,
# inputs=gr.File(label="Upload Audio or Video File"),
# outputs=gr.Markdown(label="Audio Metadata"),
# title="Audio Search by File (Support Audio or Video File)",
# description="Upload an audio or video file to identify it using ACRCloud."
# )
# # Launch the Gradio interface
# iface.launch()
import requests
import gradio as gr
import os
import json
import ffmpeg
# Function to convert video to audio using ffmpeg
def convert_video_to_audio(video_path):
try:
output_path = f"flowly_ai_audio_converter{os.path.splittext(video_path)[0]}.mp3"
ffmpeg.input(video_path).output(output_path).run()
return output_path
except Exception as e:
return f"Error converting video: {str(e)}"
# Function to recognize audio from URL or uploaded file
def recognize_audio(choice, url, file):
api_url = os.getenv("API_URL", "https://api.audd.io/").strip('"')
params = {
"return": "apple_music,spotify",
"api_token": os.getenv("API_TOKEN")
}
# Check if URL is provided
if choice == "URL":
if not url:
return "Please enter a valid URL."
params['url'] = url
response = requests.post(api_url, data=params)
# Check if file is uploaded
elif choice == "Upload File":
if not file:
return "Please upload a valid audio file."
# Check if the uploaded file is a video (e.g., mp4)
file_extension = file.split('.')[-1].lower()
audio_file_path = file
video_formats = [data.upper() for data in (sorted(['3GP', 'ASF', 'AVI', 'DIVX', 'FLV', 'M2TS', 'M4V', 'MKV', 'MOV', 'MP4', 'MPEG', 'MPG', 'MTS', 'TS', 'VOB', 'WEBM', 'WMV', 'XVID'])) if data not in ['3GP', 'DIVX', 'XVID']]
if file_extension in video_formats:
# Convert video to audio file (mp3 format)
audio_file_path = convert_video_to_audio(file)
if audio_file_path.startswith("Error"):
return audio_file_path
# If it's already an audio file, use it as is
with open(audio_file_path, "rb") as f:
response = requests.post(api_url, data=params, files={'file': f})
else:
return "Please select a method (URL or Upload File)."
# Parse the response into a structured format
try:
data = response.json()
# Check if there's an error in the response
if data.get("status") == "error":
error_message = data.get("error", {}).get("error_message", "Unknown error.")
return f"""
### Song recognition failed
{error_message}
"""
result = data.get('result', {})
artist = result.get('artist', 'Unknown Artist')
title = result.get('title', 'Unknown Title')
album = result.get('album', 'Unknown Album')
release_date = result.get('release_date', 'Unknown Date')
song_link = result.get('song_link', '')
apple_music_link = result.get('apple_music', {}).get('url', '')
spotify_link = result.get('spotify', {}).get('external_urls', {}).get('spotify', '')
markdown_output = f"""
### Song Recognition Result
- **Title**: {title}
- **Artist**: {artist}
- **Album**: {album}
- **Release Date**: {release_date}
[Listen on Apple Music]({apple_music_link})
[Listen on Spotify]({spotify_link})
#### Song Link:
[Click here to listen]({song_link})
"""
return markdown_output
except Exception as e:
return f"Error parsing response: {str(e)}"
# Gradio Interface
interface = gr.Interface(
fn=recognize_audio,
inputs=[
gr.Radio(["URL", "Upload File"], label="Select Input Method"),
gr.Textbox(label="Enter Audio URL", placeholder="https://example.com/audio.mp3"),
gr.File(label="Upload Audio or Video File", type="filepath") # Menggunakan filepath agar sesuai dengan Gradio
],
outputs=gr.Markdown(label="Recognition Result"),
title="Audio Recognition",
description="Choose a method: Upload an audio/video file or enter a URL to identify the song."
)
# Run Gradio App
if __name__ == "__main__":
interface.launch()
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