kolzchut-ragbot 1.7.2

A search engine using machine learning models and Elasticsearch for advanced document retrieval.

kolzchut-ragbot

Overview

This project is a search engine that uses machine learning models and Elasticsearch to provide advanced document retrieval. You can use kolzchut-ragbot to demonstrate the engine's document retrieval abilities.

Features

• Document representation and validation
• Document embedding and indexing in Elasticsearch
• Advanced search using machine learning model
• Integration with LLM (Large Language Model) client for query answering

Installation

From PyPI

pip install kolzchut-ragbot

From Source

1. Clone the repository:

   git clone https://github.com/shmuelrob/rag-bot.git
   cd rag-bot
   

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows use: venv\Scripts\activate
   

3. Install the required dependencies:

   pip install -r requirements.txt
   

Configuration

Set the following environment variables:

• ES_EMBEDDING_INDEX: The name of the Elasticsearch index for embeddings.
• TOKENIZER_LOCATION: The location of the tokenizer model.