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A Python implementation of a naive RAG system that recommends job positions based on user-submitted CVs in PDF format

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jobs-rag

Setup

Create a virtual environment:

> python -m venv venv

Activate the virtual environment:

> source venv/bin/activate

Install the dependencies:

> pip install -r requirements.txt

Fill .env file with Pinecone API key. There is a .env.example file to guide you.

Requirements

You will also need to have Ollama running on your local computer. You can get ollama from here. Be mindful the current code uses the llama3 model (8 billion parameters). The authors are not be responsible for any broken computers.

In Windows, after executing the downloaded .exe file, open a Command Prompt and run the following command

ollama run llama3

Running the code

  1. Execute load_jobs.py to import job data from the directory specified by the JOBS_FOLDER environment variable into Pinecone. This action will generate a Pinecone index named according to the INDEX_NAME environment variable.
  2. Run recommend_jobs.py to get recommendations for a job.

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A Python implementation of a naive RAG system that recommends job positions based on user-submitted CVs in PDF format

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