A search engine using machine learning models and Elasticsearch for advanced document retrieval.
Project description
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
-
Clone the repository:
git clone https://github.com/shmuelrob/rag-bot.git cd rag-bot
-
Create a virtual environment and activate it:
python -m venv venv source venv/bin/activate # On Windows use: venv\Scripts\activate
-
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.
Project details
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