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@@ -28,8 +28,39 @@ The application follows a sequence of steps to deliver Taylor Swift songs matchi
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  - **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.
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  ## Setup instructions
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- --TODO--
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  <small>_DISCLAIMER_: This project is 200% inspired by Francesco's [FairyTaleDJ](https://github.com/FrancescoSaverioZuppichini/FairytaleDJ). </small>
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  - **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.
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  ## Setup instructions
 
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+ ### Checkout the repo
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+ Clone the repository using the following command:
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+ ```
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+ git clone https://huggingface.co/spaces/mchockal/TaylorSwiftDJ
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+ ```
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+
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+ ### Set Environment Variables
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+ You'll need to set the following variables in the `env_vars.env` file:
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+
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+ ```dotenv
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+ OPENAI_API_KEY=
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+ ACTIVELOOP_TOKEN=
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+ ACTIVELOOP_ORG_ID=
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+ MODEL = "text-embedding-ada-002"
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+ DATASET = <your_vector_space_for_emotions>
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+ UPSTASH_URL=
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+ UPSTASH_PASSWORD=
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+ USE_STORAGE="False"
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+ ROOT=
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+ ```
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+
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+ ### Install Dependencies
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+ Install the required dependencies using the following command:
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+ ```
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+ pip install -r requirements.txt
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+ ```
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+
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+ ### Run the Streamlit App
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+ Launch the Streamlit app using the following command:
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+ ```
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+ streamlit run app.py
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+ ```
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  <small>_DISCLAIMER_: This project is 200% inspired by Francesco's [FairyTaleDJ](https://github.com/FrancescoSaverioZuppichini/FairytaleDJ). </small>
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