Create a few basic tests

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Debanjum Singh Solanky 2021-08-17 03:27:16 -07:00
parent af9660f28e
commit 569e30b1c8
5 changed files with 158 additions and 1 deletions

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- sentence-transformers - sentence-transformers
- fastapi - fastapi
- uvicorn - uvicorn
- pytest

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src/tests/__init__.py Normal file
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* Emacs Semantic Search
/An Emacs interface for [[https://github.com/debanjum/semantic-search][semantic-search]]/
** Requirements
- Install and Run [[https://github.com/debanjum/semantic-search][semantic-search]]
** Installation
- Direct Install
- Put ~semantic-search.el~ in your Emacs load path. For e.g ~/.emacs.d/lisp
- Load via ~use-package~ in your ~/.emacs.d/init.el or .emacs file by adding below snippet
#+begin_src elisp
;; Org-Semantic Search Library
(use-package semantic-search
:load-path "~/.emacs.d/lisp/semantic-search.el"
:bind ("C-c s" . 'semantic-search))
#+end_src
- Use [[https://github.com/quelpa/quelpa#installation][Quelpa]]
- Ensure [[https://github.com/quelpa/quelpa#installation][Quelpa]], [[https://github.com/quelpa/quelpa-use-package#installation][quelpa-use-package]] are installed
- Add below snippet to your ~/.emacs.d/init.el or .emacs config file and execute it.
#+begin_src elisp
;; Org-Semantic Search Library
(use-package semantic-search
:quelpa (semantic-search :fetcher url :url "https://raw.githubusercontent.com/debanjum/semantic-search/master/interface/emacs/semantic-search.el")
:bind ("C-c s" . 'semantic-search))
#+end_src
** Usage
1. Call ~semantic-search~ using keybinding ~C-c s~ or ~M-x semantic-search~
2. Enter Query in Natural Language
e.g "What is the meaning of life?" "What are my life goals?"
3. Wait for results
*Note: It takes about 15s on a Mac M1 and a ~100K lines corpus of org-mode files*
4. (Optional) Narrow down results further
Include/Exclude specific words from results by adding to query
e.g "What is the meaning of life? -god +none"

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* 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 [[./interface/emacs/semantic-search.el][Emacs]], API or Commandline
** Dependencies
- Python3
- [[https://docs.conda.io/en/latest/miniconda.html#latest-miniconda-installer-links][Miniconda]]
** Install
#+begin_src shell
git clone https://github.com/debanjum/semantic-search && cd semantic-search
conda env create -f environment.yml
conda activate semantic-search
#+end_src
** Run
Load ML model, generate embeddings and expose API to query specified org-mode files
#+begin_src shell
python3 main.py --input-files ~/Notes/Schedule.org ~/Notes/Incoming.org --verbose
#+end_src
** Use
- *Semantic Search via Emacs*
- [[https://github.com/debanjum/semantic-search/tree/master/interface/emacs#installation][Install]] [[./interface/emacs/semantic-search.el][semantic-search.el]]
- Run ~M-x semantic-search <user-query>~ or Call ~C-c C-s~
- *Semantic Search via API*
- Query: ~GET~ [[http://localhost:8000/search?q=%22what%20is%20the%20meaning%20of%20life%22][http://localhost:8000/search?q="What is the meaning of life"]]
- Regenerate Embeddings: ~GET~ [[http://localhost:8000/regenerate][http://localhost:8000/regenerate]]
- [[http://localhost:8000/docs][Semantic Search API Docs]]
- *Call Semantic Search via Python Script Directly*
#+begin_src shell
python3 search_types/asymmetric.py \
--compressed-jsonl .notes.jsonl.gz \
--embeddings .notes_embeddings.pt \
--results-count 5 \
--verbose \
--interactive
#+end_src
** Acknowledgments
- [[https://huggingface.co/sentence-transformers/msmarco-MiniLM-L-6-v3][MiniLM Model]] for Asymmetric Text Search. See [[https://www.sbert.net/examples/applications/retrieve_rerank/README.html][SBert Documentation]]
- [[https://github.com/openai/CLIP][OpenAI CLIP Model]] for Image Search. See [[https://www.sbert.net/examples/applications/image-search/README.html][SBert Documentation]]
- Charles Cave for [[http://members.optusnet.com.au/~charles57/GTD/orgnode.html][OrgNode Parser]]

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src/tests/test_main.py Normal file
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# Standard Modules
from pathlib import Path
# External Packages
import pytest
from fastapi.testclient import TestClient
# Internal Packages
from main import app, cli
from search_type import asymmetric
# Arrange
# ----------------------------------------------------------------------------------------------------
client = TestClient(app)
input_files = [Path('tests/data/main_readme.org'), Path('tests/data/interface_emacs_readme.org')]
input_filter = None
compressed_jsonl = Path('tests/data/.test.jsonl.gz')
embeddings = Path('tests/data/.test_embeddings.pt')
regenerate = False
verbose = 1
# ----------------------------------------------------------------------------------------------------
def test_asymmetric_setup():
# Act
entries, corpus_embeddings, bi_encoder, cross_encoder, top_k = asymmetric.setup(input_files, input_filter, compressed_jsonl, embeddings, regenerate, verbose)
# Assert
assert len(entries) == 10
assert len(corpus_embeddings) == 10
# ----------------------------------------------------------------------------------------------------
def test_cli_default():
# Act
args = cli(['--input-files=tests/data/test.org'])
# Assert
assert args.input_files == ['tests/data/test.org']
assert args.input_filter == None
assert args.compressed_jsonl == Path('.notes.jsonl.gz')
assert args.embeddings == Path('.notes_embeddings.pt')
assert args.regenerate == False
assert args.verbose == 0
# ----------------------------------------------------------------------------------------------------
def test_cli_set_by_user():
# Act
actual_args = cli(['--input-files=tests/data/test.org',
'--input-filter=tests/data/*.org',
'--compressed-jsonl=tests/data/.test.jsonl.gz',
'--embeddings=tests/data/.test_embeddings.pt',
'--regenerate',
'-vvv'])
# Assert
assert actual_args.input_files == ['tests/data/test.org']
assert actual_args.input_filter == 'tests/data/*.org'
assert actual_args.compressed_jsonl == Path('tests/data/.test.jsonl.gz')
assert actual_args.embeddings == Path('tests/data/.test_embeddings.pt')
assert actual_args.regenerate == True
assert actual_args.verbose == 3