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d5597442f4
Details
- Rename method query_* to query in search_types for standardization
- Wrapping Config code in classes simplified mocking test config
- Reduce args beings passed to a function by passing it as single
argument wrapped in a class
- Minimize setup in main.py:__main__. Put most of it into functions
These functions can be mocked if required in tests later too
Setup Flow:
CLI_Args|Config_YAML -> (Text|Image)SearchConfig -> (Text|Image)SearchModel
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-searchRun
Load ML model, generate embeddings and expose API to query specified org-mode files
python3 src/main.py -c=sample_config.yml -vvUse
-
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-searchAcknowledgments
- 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