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Debanjum Singh Solanky a6aef62a99 Create Basic Landing Page to Query Semantic Search and Render Results 
- Allow viewing image results returned by Semantic Search.
  Until now there wasn't any interface within the app to view image
  search results. For text results, we at least had the emacs interface

- This should help with debugging issues with image search too
  For text the Swagger interface was good enough
2022-07-16 03:36:19 +04:00
.github/workflows Run build on PR 2022-07-04 18:09:47 -04:00
config Add separate conda environment.yml for osx-arm64 2022-07-14 23:16:49 +04:00
src Create Basic Landing Page to Query Semantic Search and Render Results 2022-07-16 03:36:19 +04:00
tests Handle unparseable date range passed via date filter in query 2022-07-14 22:47:23 +04:00
views Fix input text behavior for null/empty value fields 2021-12-04 10:45:48 -05:00
.dockerignore Make Docker ignore unnecessary files 2022-06-29 22:29:34 +04:00
.gitignore Create Basic Landing Page to Query Semantic Search and Render Results 2022-07-16 03:36:19 +04:00
demo.mp4 Add demo of semantic search to repository 2022-05-14 04:29:25 -04:00
docker-compose.yml Correct syntax of memory limit in docker-compose.yml 2022-07-06 20:07:11 -04:00
Dockerfile Add specific version for Python packages and downgrade miniconda Docker image to potentially fix build issues 2022-07-04 18:01:55 -04:00
LICENSE Add Readme, License. Update .gitignore 2021-08-15 22:52:37 -07:00
README.org Fix formatting for pytest command 2022-07-08 10:18:26 -04:00

README.org

https://github.com/debanjum/semantic-search/actions/workflows/test.yml/badge.svg https://github.com/debanjum/semantic-search/actions/workflows/build.yml/badge.svg

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

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

Run Unit tests 

pytest

Upgrade 

  docker-compose build --pull

Troubleshooting

  • Symptom: Errors out with "Killed" in error message

  • 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
  1. Install Python3 [Required]
  2. Install Conda [Required]

  3. 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 of sample_config.yml

  • To run application on test data, update file paths containing /data/ to tests/data/ in sample_config.yml

    • Example replace /data/notes/*.org with tests/data/notes/*.org
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