https://github.com/aravind-manoj/semantic-search-engine
A simple semantic search engine in Python
https://github.com/aravind-manoj/semantic-search-engine
api backend huggingface-transformers python search-engine semantic
Last synced: 11 months ago
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A simple semantic search engine in Python
- Host: GitHub
- URL: https://github.com/aravind-manoj/semantic-search-engine
- Owner: aravind-manoj
- Created: 2024-08-11T08:49:03.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-08-11T08:57:39.000Z (almost 2 years ago)
- Last Synced: 2025-04-02T14:11:12.672Z (about 1 year ago)
- Topics: api, backend, huggingface-transformers, python, search-engine, semantic
- Language: Python
- Homepage:
- Size: 3.91 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Semantic Search Engine
This project is a simple semantic search engine built using the all-mpnet-base-v2 AI model, designed for efficient sentence phrasing and semantic similarity search.
## Features
Semantic Search: Finds the most semantically similar sentences or phrases to a given query.
Efficient Encoding: Utilizes the all-mpnet-base-v2 model to encode sentences into dense vectors for comparison.
Python-Based: Built entirely in Python for easy integration and use.
Installation
To use this semantic search engine, you'll need to have Python installed. You can install the necessary dependencies using pip:
```
pip install -r requirements.txt
```
Note: Ensure that you have a compatible version of Python (3.7 or higher).
## Usage
To use the search engine, simply run the main script with your query:
```
python main.py --query "your search phrase"
```
The script will return the most semantically similar results based on the all-mpnet-base-v2 model.
## Model
This project leverages the all-mpnet-base-v2 model from Hugging Face's Transformers library. This model is known for its efficiency in sentence embedding, making it a great choice for semantic search tasks.
## Contributing
Contributions are welcome! Please fork the repository and submit a pull request with your improvements.
## Acknowledgments
Hugging Face for providing the all-mpnet-base-v2 model.
The Python community for their continuous support and contributions to open-source projects.