app.py

import streamlit as st
from streamlit import session_state as session
from src.laion_clap.inference import AudioEncoder
# from src.utils.spotify import SpotifyHandler, SpotifyAuthentication
import pandas as pd
from dotenv import load_dotenv
from langchain.llms import CTransformers, Ollama
from src.llm.chain import LLMChain
from pymongo.mongo_client import MongoClient
import os

st.set_page_config(page_title="Curate me a playlist", layout="wide")
load_dotenv()

def load_llm_pipeline():
    ctransformers_config = {
        "max_new_tokens": 3000,
        "temperature": 0,
        "top_k": 1,
        "top_p": 1,
        "context_length": 2800
        }

    llm = CTransformers(
        model="TheBloke/Mistral-7B-Instruct-v0.1-GGUF", 
        model_file="mistral-7b-instruct-v0.1.Q5_K_M.gguf",
        config=ctransformers_config
        )
    # llm = Ollama(temperature=0, model="mistral:7b-instruct-q8_0", top_k=1, top_p=1, num_ctx=2800)
    chain = LLMChain(llm)
    return chain

@st.cache_resource
def load_resources():
    password = os.getenv("MONGODB_PASSWORD")
    url = os.getenv("MONGODB_URL")
    uri = f"mongodb+srv://berkaygkv:{password}@{url}/?retryWrites=true&w=majority"
    client = MongoClient(uri)
    db = client.spoti
    mongo_db_collection = db.saved_tracks
    recommender = AudioEncoder(mongo_db_collection)
    recommender.load_existing_audio_vectors()
    llm_pipeline = load_llm_pipeline()
    return recommender, llm_pipeline


recommender, llm_pipeline = load_resources()

st.title("""Curate me a Playlist.""")
session.text_input = st.text_input(label="Describe a playlist")
session.slider_count = st.slider(label="Track counts", min_value=5, max_value=35, step=5)
buffer1, col1, col2, buffer2 = st.columns([1.45, 1, 1, 1])

is_clicked = col1.button(label="Curate")
if is_clicked:
    output = llm_pipeline.process_user_description(session.text_input)
    song_list = []
    for _, song_desc in output:
        print(song_desc)
        ranking = recommender.list_top_k_songs(song_desc, k=15)
        song_list += ranking
    
    dataframe = pd.DataFrame(song_list).sort_values("score", ascending=False).drop_duplicates(subset=["track_id"]).drop(columns=["track_id"]).reset_index(drop=True)
    dataframe = dataframe.iloc[:session.slider_count]
    st.data_editor(
        dataframe,
        column_config={
            "link": st.column_config.LinkColumn(
                "link",
                # help="The top trending Streamlit apps",
                # validate="^https://[a-z]+\.streamlit\.app$",
                # max_chars=100,
                    )
                        },
        hide_index=False,
        use_container_width=True
    )


    # with st.form(key="spotiform"):
    #     st.form_submit_button(on_click=authenticate_spotify, args=(session.access_url, ))
    #     st.markdown(session.access_url)