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* Update README with more context. * Add links and resources
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[![Built with Cookiecutter](https://img.shields.io/badge/built%20with-Cookiecutter-ff69b4.svg?logo=cookiecutter)](https://github.com/cookiecutter/cookiecutter) | ||
[![Built with Cookiecutter](https://img.shields.io/badge/built%20with-Cookiecutter-ff69b4.svg?logo=cookiecutter)](https://github.com/thinknimble/tn-spa-bootstrapper) | ||
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# Vector Demonstration | ||
# AI-Enabled Search Engine using LLM Embeddings, Django, and pgvector | ||
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A lot of people have asked us for ideas of how they can leverage Large Language Models (LLMs) for their business applications. A common example is to use the native language comprehension capabilities of LLMs to find matching content. This makes LLMs an excellent tool for search! | ||
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This repo demonstrates a prototype application that enables searching for job descriptions using an unstructured, English-language description of a job seeker. | ||
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## Watch the Demo on Youtube | ||
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[![Video: How We're Building AI Search Engines using LLM Embeddings](http://img.youtube.com/vi/ZCPUmC37HLU/0.jpg)](http://www.youtube.com/watch?v=ZCPUmC37HLU "How We're Building AI Search Engines using LLM Embeddings") | ||
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## Links & Resources | ||
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- https://www.sbert.net/ - Sentence Transformers package for Python | ||
- https://github.com/pgvector/pgvector - Vector database plugin for PostgreSQL | ||
- https://huggingface.co/spaces/mteb/leaderboard - The "Massive Text Embedding" leaderboard from HuggingFace. Look at this to find models you can use to generate embeddings. | ||
- https://www.djangoproject.com/ | ||
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## Setup | ||
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### Docker | ||
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If this is your first time... | ||
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1. [Install Docker](https://www.docker.com/) | ||
1. Run `pipenv lock` to generate a Pipfile.lock | ||
1. Run `cd client && npm install` so you have node_modules available outside of Docker | ||
1. Back in the root directory, run `make build` | ||
1. `make run` to start the app | ||
1. If the DB is new, run `make create-test-data` | ||
1. SuperUser `[email protected]` with credentials from your `.env` | ||
1. User `[email protected]` with credentials from your `.env` is used by the Cypress | ||
tests | ||
1. SuperUser `[email protected]` with credentials from your `.env` | ||
1. User `[email protected]` with credentials from your `.env` is used by the Cypress | ||
tests | ||
1. View other available scripts/commands with `make commands` | ||
1. `localhost:8080` to view the app. | ||
1. `localhost:8000/staff/` to log into the Django admin | ||
1. `localhost:8000/api/docs/` to view backend API endpoints available for frontend development | ||
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### Backend | ||
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If not using Docker... | ||
See the [backend README](server/README.md) | ||
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### Frontend | ||
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If not using Docker... | ||
See the [frontend README](client/README.md) | ||
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## Testing & Linting Locally | ||
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1. `pipenv install --dev` | ||
1. `pipenv run pytest server` | ||
1. `pipenv run black server` | ||
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