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Utilising the concepts of LLM from Langchain and integrating Hugging Face model and Google Gemini AI chatbot to understand emotional sentiments of lyrics and develop a pesudo-RAG that will return quotes from BTS songs

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HarshiniR4/Lyric_LLM_Project

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# Lyric_LLM_Project

Aim:

Developing an RAG using the Langchain LLMs and HuggingFaceHub model to perform sentiment analysis on BTS songs lyrics translations and suggest a playlist and set of quotes from the songs according to the user's emotions.

Libraries Required:

  • Langchain
  • NLTK
  • HuggingFaceHub
  • Streamlit
  • Beautifulsoup
  • Pandas
  • JSON

Procedure:

  1. Scrape data fromDoolset Bangtan Lyric Translations to obtain all BTS songs and their lyrics with translations
  2. Clean the scraped data and extract only the translations into a JSON
  3. Create two Langchain LLMs using the HuggingFaceHub model to perform sentimental analysis and obtain
    • emotion for every line translation for every song in the JSON
    • the overall emotion of each song
  4. Save the results in a consolidated dataset
  5. Using Streamlit obtain user input for any emotions and derive the appropriate playlist and quotes for the user based on the emotions

How to run:

Clone the repository and run the emotion_chatbot.py file using Streamlit

streamlit run emotion_chatbot.py

Output

Streamlit Output image

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Utilising the concepts of LLM from Langchain and integrating Hugging Face model and Google Gemini AI chatbot to understand emotional sentiments of lyrics and develop a pesudo-RAG that will return quotes from BTS songs

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