.github/workflows | ||
config | ||
src | ||
tests | ||
views | ||
.dockerignore | ||
.gitignore | ||
demo.mp4 | ||
docker-compose.yml | ||
LICENSE | ||
README.org |
Semantic Search
Allow natural language search on user content like notes, images, transactions using transformer ML models
User can interface with semantic-search via the API or Emacs. All search is done locally*
Demo
Setup
1. Clone
git clone https://github.com/debanjum/semantic-search && cd semantic-search
2. Configure
- [Required] Update docker-compose.yml to mount your images, org-mode notes and beancount directories
- [Optional] Edit application configuration in sample_config.yml
3. Run
docker-compose up -d
Note: The first run will take time. Let it run, it's mostly not hung, just generating embeddings
Use
-
Semantic Search via API
-
Semantic Search via Emacs
- Install semantic-search.el
- Run
M-x semantic-search <user-query>
Upgrade
docker-compose build
Troubleshooting
-
Symptom: Errors out with "Killed" in error message
- Fix: Increase RAM available to Docker Containers in Docker Settings
- Refer: StackOverflow Solution, Configure Resources on Docker for Mac
-
Symptom: Errors out complaining about Tensors mismatch, null etc
- Mitigation: Delete content-type > image section from docker_sample_config.yml
Miscellaneous
-
The experimental chat API endpoint uses the OpenAI API
- It is disabled by default
- To use it add your
openai-api-key
to config.yml
Development Setup
Setup on Local Machine
1. Install Dependencies
- Install Python3 [Required]
- Install Conda [Required]
-
Install Exiftool [Optional]
sudo apt-get -y install libimage-exiftool-perl
2. Install Semantic Search
git clone https://github.com/debanjum/semantic-search && cd semantic-search
conda env create -f config/environment.yml
conda activate semantic-search
3. Configure
- Configure files/directories to search in
content-type
section ofsample_config.yml
-
To run application on test data, update file paths containing
/data/
totests/data/
insample_config.yml
- Example replace
/data/notes/*.org
withtests/data/notes/*.org
- Example replace
4. Run
Load ML model, generate embeddings and expose API to query notes, images, transactions etc specified in config YAML
python3 -m src.main -c=config/sample_config.yml -vv
Upgrade On Local Machine
cd semantic-search
git pull origin master
conda deactivate semantic-search
conda env update -f config/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