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35b46849a2f2f9c25b6d917cf03369e673e8056e
Skip Flaky Image Search Test
Semantic Search
Allow natural language search on user content like notes, images, transactions using transformer based models
All data is processed locally. User can interface with semantic-search app via Emacs, API or Commandline
Dependencies
- Python3
- Miniconda
Install
git clone https://github.com/debanjum/semantic-search && cd semantic-search
conda env create -f environment.yml
conda activate semantic-search
* Install Environment Dependencies
sudo apt-get -y install libimage-exiftool-perl
Configure
Configure application search types and their underlying data source/files in sample_config.yml
Use the sample_config.yml as reference
Run
Load ML model, generate embeddings and expose API to query notes, images, transactions etc specified in config YAML
python3 -m src.main -c=sample_config.yml -vv
Use
-
Semantic Search via Emacs
- Install semantic-search.el
- Run
M-x semantic-search <user-query>
-
Semantic Search via API
- Query:
GEThttp://localhost:8000/search?q="What is the meaning of life&t=notes" - Regenerate Embeddings:
GEThttp://localhost:8000/regenerate?t=image - Semantic Search API Docs
- Query:
Upgrade
cd semantic-search
git pull origin master
conda env update -f environment.yml
conda activate semantic-search
Acknowledgments
- MiniLM Model for Asymmetric Text Search. See SBert Documentation
- OpenAI CLIP Model for Image Search. See SBert Documentation
- Charles Cave for OrgNode Parser
- Sven Marnach for PyExifTool
Languages
Python
51%
TypeScript
36.1%
CSS
4.1%
HTML
3.2%
Emacs Lisp
2.4%
Other
3.1%