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| title: TaylorSwiftDJ | |
| emoji: 🌟 | |
| colorFrom: pink | |
| colorTo: indigo | |
| sdk: streamlit | |
| sdk_version: 1.26.0 | |
| app_file: app.py | |
| pinned: false | |
| license: creativeml-openrail-m | |
| # 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 | |
| ### Checkout the repo | |
| Clone the repository using the following command: | |
| ``` | |
| git clone https://huggingface.co/spaces/mchockal/TaylorSwiftDJ | |
| ``` | |
| ### Set Environment Variables | |
| You'll need to set the following variables in the `env_vars.env` file: | |
| ```dotenv | |
| OPENAI_API_KEY= | |
| ACTIVELOOP_TOKEN= | |
| ACTIVELOOP_ORG_ID= | |
| MODEL = "text-embedding-ada-002" | |
| DATASET = <your_vector_space_for_emotions> | |
| UPSTASH_URL= | |
| UPSTASH_PASSWORD= | |
| USE_STORAGE="False" | |
| ROOT= | |
| ``` | |
| ### Install Dependencies | |
| Install the required dependencies using the following command: | |
| ``` | |
| pip install -r requirements.txt | |
| ``` | |
| ### Run the Streamlit App | |
| Launch the Streamlit app using the following command: | |
| ``` | |
| streamlit run app.py | |
| ``` | |
| <small>_DISCLAIMER_: This project is 200% inspired by Francesco's [FairyTaleDJ](https://github.com/FrancescoSaverioZuppichini/FairytaleDJ). </small> | |