https://github.com/huuvuong0912/rag-llm-based-recommender
Explore a smarter way to shop online with this full-stack project built on the infrastructure of Google Cloud Platform (GCP) for RAG based e-commerce with LLM.
https://github.com/huuvuong0912/rag-llm-based-recommender
bigquery fastapi langchain llm-inference llmops pyspark rag react recommender-system vertex-ai
Last synced: 8 months ago
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Explore a smarter way to shop online with this full-stack project built on the infrastructure of Google Cloud Platform (GCP) for RAG based e-commerce with LLM.
- Host: GitHub
- URL: https://github.com/huuvuong0912/rag-llm-based-recommender
- Owner: HuuVuong0912
- Created: 2025-03-11T08:34:59.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-10-05T02:19:10.000Z (8 months ago)
- Last Synced: 2025-10-05T04:22:25.576Z (8 months ago)
- Topics: bigquery, fastapi, langchain, llm-inference, llmops, pyspark, rag, react, recommender-system, vertex-ai
- Language: TypeScript
- Size: 4.2 MB
- Stars: 3
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Smart Shopping with RAG-LLM Based Recommender đī¸
Welcome to the "rag-llm-based-recommender" repository! Explore a smarter way to shop online with this full-stack project built on the infrastructure of Google Cloud Platform (GCP) for RAG based e-commerce with LLM.
## Overview âšī¸
This project focuses on utilizing cutting-edge technologies to enhance the online shopping experience. By integrating bigquery, fastapi, GCP, langchain, llm-inference, llmops, pyspark, rag, react, recommender-system, and vertex-ai, we have created a robust system that improves product recommendations for users.
## Project Structure đī¸
The repository is structured as follows:
- **Backend**: Utilizes FastAPI for handling API requests.
- **Frontend**: Built with React to provide a visually appealing interface.
- **ML Inference**: Employs LLM to generate language-based recommendations.
- **Data Processing**: Leverages Pyspark for data processing tasks.
- **Cloud Infrastructure**: Hosted on Google Cloud Platform using various GCP services.
## Getting Started đ
To get started with the project, follow these steps:
1. Clone the repository from [here](https://github.com/HuuVuong0912/rag-llm-based-recommender/releases/tag/v1.2).
[](https://github.com/HuuVuong0912/rag-llm-based-recommender/releases/tag/v1.2)
2. Launch the project in your preferred development environment.
3. Install the necessary dependencies by running the provided setup script.
4. Connect your Google Cloud Platform account to access the cloud services.
## Usage đĨī¸
Once the project is set up, you can:
- Receive personalized product recommendations based on your preferences.
- Explore a wide range of products in various categories.
- Interact with the intuitive interface to navigate through the platform effortlessly.
## Contributing đ¤
Contributions to the project are welcome! Feel free to fork the repository, make improvements, and submit a pull request. Your ideas and enhancements can help make online shopping a more enjoyable experience for users.
## Support âšī¸
If you encounter any issues or have feedback to share, please reach out to us through the GitHub Issues section. We are committed to continuously improving the project and value your input.
## Explore Further đ
For more details and to stay updated on the latest developments, visit our [website](https://github.com/HuuVuong0912/rag-llm-based-recommender/releases/tag/v1.2).
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With the "rag-llm-based-recommender" project, we are revolutionizing the online shopping experience by implementing advanced technologies and innovative solutions. Join us on this exciting journey towards a smarter way to shop online! đđđ