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2.2 KiB
2.2 KiB
Semantic Search
Allow natural language search on user content like notes, images 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
Run
Load ML model, generate embeddings and expose API to query specified org-mode files
python3 main.py --input-files ~/Notes/Schedule.org ~/Notes/Incoming.org --verbose
Use
-
Semantic Search via Emacs
- Install semantic-search.el
- Run
M-x semantic-search <user-query>
or CallC-c C-s
-
Semantic Search via API
- Query:
GET
http://localhost:8000/search?q="What is the meaning of life" - Regenerate Embeddings:
GET
http://localhost:8000/regenerate - Semantic Search API Docs
- Query:
-
Call Semantic Search via Python Script Directly
python3 search_types/asymmetric.py \ --compressed-jsonl .notes.jsonl.gz \ --embeddings .notes_embeddings.pt \ --results-count 5 \ --verbose \ --interactive
Acknowledgments
- MiniLM Model for Asymmetric Text Search. See SBert Documentation
- OpenAI CLIP Model for Image Search. See SBert Documentation
- Charles Cave for OrgNode Parser