https://github.com/francescosaveriozuppichini/fairytaledj
You got a friend in me
https://github.com/francescosaveriozuppichini/fairytaledj
chatgpt llms machine-learning programming python
Last synced: about 1 month ago
JSON representation
You got a friend in me
- Host: GitHub
- URL: https://github.com/francescosaveriozuppichini/fairytaledj
- Owner: FrancescoSaverioZuppichini
- Created: 2023-05-15T16:17:45.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-05-24T18:31:27.000Z (about 2 years ago)
- Last Synced: 2025-05-07T23:08:13.975Z (about 1 month ago)
- Topics: chatgpt, llms, machine-learning, programming, python
- Language: Python
- Homepage: https://huggingface.co/spaces/Francesco/FairytaleDJ
- Size: 1.27 MB
- Stars: 28
- Watchers: 2
- Forks: 11
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
---
title: "FairytaleDJ"
emoji: "🔮"
colorFrom: "indigo"
colorTo: "purple"
sdk: "streamlit"
sdk_version: "1.19.0"
app_file: app.py
pinned: false
---
# FairytaleDJ 🎵🏰🔮
The app is on [hugging face spaces](https://huggingface.co/spaces/Francesco/FairytaleDJ) 🤗
This app takes a user input and suggestes songs that matches its emotions/vibes.
Made with [DeepLake](https://www.deeplake.ai/) 🚀 and [LangChain](https://python.langchain.com/en/latest/index.html) 🦜⛓️
We also used [upstash](https://upstash.com/) to store user inputs/emotions and recommended songs
## How it works
The application follows a sequence of steps to deliver Disney 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](Deep Lake Vector Store in LangChain). This database houses Disney 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.
## Run it
Clone this repo.
create a `venv`
```
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
```
You will need the following `.env` file
```bash
OPENAI_API_KEY=
ACTIVELOOP_TOKEN=
ACTIVELOOP_ORG_ID=zuppif
UPSTASH_URL=
UPSTASH_PASSWORD=
```
If you **don't want to use upstash** set the `USE_STORAGE=False`
Then
```
streamlit run app.py
```
Then navitage to `http://192.168.1.181:8501`