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from ArtistCoherencyModel import ArtistCoherencyModel
import streamlit as st
import pandas as pd
from LyricGeneratorModel import LyricGeneratorModel
@st.cache_resource
def get_artists():
artists_df = pd.read_csv("artists.csv")
return list(artists_df["name"])
@st.cache_resource
def get_evaluator_model():
lyric_evaluator_model = None
with st.spinner("Loading Evaluation Model..."):
lyric_evaluator_model = ArtistCoherencyModel.from_pretrained(
"tjl223/artist-coherency-ensemble"
)
st.success("Finished Loading Evaluation Model")
return lyric_evaluator_model
@st.cache_resource
def get_generator_model():
lyric_generator_model = None
with st.spinner("Loading Generator Model..."):
lyric_generator_model = LyricGeneratorModel(
"tjl223/llama2-qlora-lyric-generator"
)
st.success("Finished Loading Generator Model")
return lyric_generator_model
lyric_evaluator_model = get_evaluator_model()
lyric_generator_model = get_generator_model()
artist_names_list = get_artists()
generator_title = st.title("Lyric Generator")
artist_name_for_generator = st.selectbox("Artist", artist_names_list)
song_title = st.text_input("Song Title")
song_description = st.text_area("Song Description")
if st.button("Submit"):
prompt = f"[Song Title] {song_title}\n[Song Artist] {artist_name_for_generator}\n[Song Description] {song_description}"
print(f"Prompt: {prompt}")
lyrics = ""
with st.spinner("Generating Lyrics..."):
lyrics = lyric_generator_model.generate_lyrics(prompt, 1000)
st.success("Finished Generating Lyrics")
print(f"Lyrics: {lyrics}")
for line in lyrics.split("\n"):
if line.startswith("["):
st.markdown(f"**{line}**")
continue
elif line.strip() == "<END_OF_SONG>":
break
st.write(line)
evaluator_title = st.title("Lyric Evaluator")
artist_name_for_evaluator = st.selectbox(
"Artist", artist_names_list, key="genorator_select"
)
evaluator_song_lyrics = st.text_area("Song Lyrics")
if st.button("Submit", key="generator_submit"):
score = lyric_evaluator_model.generate_artist_coherency_score(
artist_name_for_evaluator, evaluator_song_lyrics.replace("\n\n", "\n")
)
print(f"Score: {score}")
st.write(f"Score: {score}")
predictor_title = st.title("Lyric Predictor")
predictor_song_lyrics = st.text_area("Song Lyrics", key="predictor song lyrics")
if st.button("Submit", key="predictor_submit"):
artist, artist_score = lyric_evaluator_model.predict_artist(
predictor_song_lyrics.replace("\n\n", "\n")
)
coherency, coherency_score = lyric_evaluator_model.predict_coherency(
predictor_song_lyrics.replace("\n\n", "\n")
)
print(f"Predicted {artist} with a score of {artist_score}")
st.write(f"Predicted {artist} with a score of {artist_score}")
print(f"Predicted {coherency} with a score of {coherency_score}")
st.write(f"Predicted {coherency} with a score of {coherency_score}")
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