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ae15e429b5
Prevent everything looking like code blocks due to 4 space indentations
1.6 KiB
1.6 KiB
Semantic Search
Provide natural language search on user personal content like notes, images using ML 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
Setup
Generate compressed JSONL from specified org-mode files
python3 processor/org-mode/org-to-jsonl.py \
--org-files "Schedule.org" "Incoming.org" \
--org-directory "~/Notes" \
--jsonl-file ".data/notes.jsonl" \
--compress \
--verbose
Run
Load ML model, generate embeddings and expose API interface to run user queries on above org-mode files
python3 main.py -j .data/notes.jsonl.gz -e .data/notes_embeddings.pt
Use
-
Calls Semantic Search via Emacs
M-x semantic-search "<user-query>"
C-c C-s
-
Call Semantic Search via API
-
Call Semantic Search via Python Script Directly
python3 search_types/asymmetric.py \ -j .data/notes.jsonl.gz \ -e .data/notes_embeddings.pt \ -n 5 \ --verbose \ --interactive
Acknowledgments
- Charles Cave for OrgNode Parser