---
title: Eshop Chat
emoji: 🦀
colorFrom: indigo
colorTo: gray
sdk: docker
pinned: false
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference


### How to run on your localhost? (For MAC users)
- Install Docker for MAC app to make docer enginee available to vscode
- Install vscode
- Open the project in vscode
- Create .env file only on local machine (DO NOT ADD AND PUSH IT TO GIT)
- Add openai api key to .env file: Eg. OPENAI_API_KEY=sk-WSISHD232UDDUDJHHQQTT
- Type CMD+SHIFT+P and select Dev Containers: Rebuild Container. It will create docker container environment to run the code within the container. You don't have to install any project specific packages on you local machine.
- Use menu Terminal > New Terminal, to open a shell and type following command to run chainlit server
- If everything works, then you can access the application using http://localhost:7860/ . Please note that port 7860 is required by huggingface to make our application accessible using huggingface url (after git push).
- chainlit run app.py --port 7860

### BestBuy Datasets
- https://github.com/BestBuyAPIs/open-data-set

### This app only uses first 100 product information
- It uses products.json data to create normalized categories
- Google colab is used to explore the data: https://colab.research.google.com/drive/17iPtcrdEHnqcECF6xakGB0HaWG33PzFw?usp=sharing
- It generates product spec using the product and categories features, which is then used to create vector embeddings and save in vector store (Chroma vector store)