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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 = []
# Process audio in 10-second chunks
for i in range(0, duration_ms // 1000, 10):
res = acr.recognize_by_file(file_path, i, 10)
results.append(f"**Time {i}s**: {res.strip()}")
# Full recognition result
full_result = acr.recognize_by_file(file_path, 0)
# Recognize using file buffer
with open(file_path, 'rb') as f:
buf = f.read()
buffer_result = acr.recognize_by_filebuffer(buf, 0)
# Convert JSON results to dictionary
full_result_dict = json.loads(full_result)
buffer_result_dict = json.loads(buffer_result)
# Format the results as markdown
result_md = f"""
### **Partial Results**:
{'\n'.join(results)}
### **Full Result**:
- **Track**: {full_result_dict['metadata']['music'][0]['title']}
- **Artist**: {full_result_dict['metadata']['music'][0]['artists'][0]['name']}
- **Album**: {full_result_dict['metadata']['music'][0]['album']['name']}
- **Release Date**: {full_result_dict['metadata']['music'][0]['release_date']}
- **Score**: {full_result_dict['metadata']['music'][0]['score']}%
### **Buffer Result**:
- **Track**: {buffer_result_dict['metadata']['music'][0]['title']}
- **Artist**: {buffer_result_dict['metadata']['music'][0]['artists'][0]['name']}
- **Album**: {buffer_result_dict['metadata']['music'][0]['album']['name']}
- **Release Date**: {buffer_result_dict['metadata']['music'][0]['release_date']}
- **Score**: {buffer_result_dict['metadata']['music'][0]['score']}%
"""
return gr.Markdown(result_md)
# Create Gradio interface
iface = gr.Interface(
fn=identify_audio,
inputs=gr.File(label="Upload Audio File"),
outputs=gr.Markdown(label="Audio Metadata"),
title="Audio Search by File",
description="Upload an audio file to identify it using ACRCloud."
)
# Launch the Gradio interface
iface.launch()
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