Bulking and sorting is not going to be the AI’s strong suit. Consider the method in which it generates text: It must output the most likely selections, decide at a point to switch to the other category, and then produce more.
Poll what it can answer, and compare to human evaluations:
Classify and characterize song in several areas.
Song query: “ABBA - Thank You for the Music”
Output JSON (python dictionary) with keys: [ bpm, time signature, length, tempo, mood, danceability(1-10), energy(1-10)]
Here’s a Python dictionary with the requested song characteristics for “ABBA - Thank You for the Music”:
{
"bpm": 120, # Beats Per Minute (BPM)
"time_signature": "4/4", # Time Signature (typically 4/4 for most pop songs)
"length": "4:05", # Song Length (minutes:seconds)
"tempo": "Moderate", # Tempo (e.g., Slow, Moderate, Fast)
"mood": "Joyful", # Mood/Emotion (e.g., Happy, Sad, Energetic, etc.)
"danceability": 7, # Danceability on a scale of 1 to 10 (higher values mean more danceable)
"energy": 6 # Energy on a scale of 1 to 10 (higher values indicate higher energy)
}
It has some anti-hallucination text on my made up example and more characteristics, to then let you decide if the information is “real” or “a typical answer”:
I’m sorry for any confusion, but I can’t provide real-time information or access external databases to retrieve details about a specific song that may not be well-known or in my training data, such as “Pink Tuxedo - Computers Rock My World.” However, I can help you understand how you can classify and characterize a song in several areas based on available information or by analyzing the song directly if you have access to its audio features.
Here’s a Python dictionary structure for characterizing a song based on available information:
song_info = {
"title": "Computers Rock My World",
"artist": "Pink Tuxedo",
"bpm": 120, # Beats Per Minute
"time_signature": "4/4", # Time signature
"length": "3:30", # Song length
"tempo": "Moderate", # Tempo description (e.g., Slow, Moderate, Fast)
"mood": "Energetic", # Mood or emotion of the song
"danceability": 7, # Danceability rating on a scale of 1 to 10
"energy": 8, # Energy rating on a scale of 1 to 10
"group": "Beat" # Categorization as "Beat" or "Easy"
}
print(song_info)
Please note that the actual values for BPM, time signature, length, tempo, mood, danceability, energy, and group should be determined based on the song’s specific characteristics. You may need to use music analysis tools or databases to obtain these details accurately. Additionally, the mood, danceability, energy, and group fields are subjective and may vary depending on the interpretation of the song’s characteristics.
