Update README.md

README.md

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 ---
 title: TaylorSwiftDJ
-emoji: 😻
+emoji: 🌟
 colorFrom: pink
 colorTo: indigo
 sdk: streamlit
@@ -10,4 +10,26 @@ pinned: false
 license: creativeml-openrail-m
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# TaylorSwiftDJ 🌟
+
+*<small>Made with [DeepLake](https://www.deeplake.ai/) 🚀 and [LangChain](https://python.langchain.com/en/latest/index.html) 🦜⛓️</small>*
+
+💫 Hey there Swifties! Welcome to "TaylorSwiftDJ"! 🎤🎶 \
+This streamlit powered app recommends Taylor Swift's iconic songs 'tailored'(hah! :D) to your emotions. \
+Dance, reminisce, and embrace your feelings with every beat – because life's a melody, and Taylor's your DJ. ✨ 🌈 💖
+
+  
+## How it works
+The application follows a sequence of steps to deliver Taylor Swift songs matching the user's emotions:
+- **User Input**: The application starts by collecting user's emotional state through a text input.
+- **Emotion Encoding**: The user-provided emotions are then fed to a Language Model (LLM). The LLM interprets and encodes these emotions.
+- **Similarity Search**: These encoded emotions are utilized to perform a similarity search within our [vector database](https://www.deeplake.ai/). This database houses ~130 Taylor Swift songs, each represented as emotional embeddings.
+- **Song Selection**: From the pool of top matching songs, the application randomly selects one. The selection is weighted, giving preference to songs with higher similarity scores.
+- **Song Retrieval**: The selected song's embedded player is displayed on the webpage for the user. Additionally, the LLM interpreted emotional state associated with the chosen song is displayed.
+
+## Setup instructions
+--TODO--
+
+<small>_DISCLAIMER_: This project is 200% inspired by Francesco's [FairyTaleDJ](https://github.com/FrancescoSaverioZuppichini/FairytaleDJ). </small>
+
+