Elasticsearch Management System

Overview

This project is an Elasticsearch management system with a FastAPI backend and a Streamlit frontend. It provides a user-friendly interface for managing Elasticsearch indices, documents, and performing various search operations.

Features

• Create and delete Elasticsearch indices
• Insert, update, and delete documents
• Perform text and KNN (K-Nearest Neighbors) searches
• Manage index mappings
• Create and manage embeddings for semantic search
• User-friendly Streamlit interface for easy interaction

Tech Stack

• Backend: FastAPI
• Frontend: Streamlit
• Database: Elasticsearch
• Embedding Model: [Specify the model you're using, e.g., Sentence Transformers]

Prerequisites

• Python 3.7+
• Elasticsearch 7.x or 8.x
• pip (Python package manager)

Installation

1. Clone the repository: git clone https://github.com/MohammadMdv/Elasticseach.git cd elasticsearch-management-system
2. Set up a virtual environment (optional but recommended): python -m venv venv source venv/bin/activate # On Windows use venv\Scripts\activate
3. Install the required packages: pip install -r requirements.txt
4. Set up Elasticsearch:

• Ensure Elasticsearch is installed and running on your system
• Update the Elasticsearch connection settings in app/config.py

Running the Application

1. Start the backend server: cd backend then uvicorn app.main:app --reload

2. In a new terminal, start the Streamlit frontend: cd frontend then streamlit run app.py The Streamlit interface will open in your default web browser.

API Documentation

Once the backend is running, you can access the API documentation at http://localhost:8000/docs

Usage

1. Use the Streamlit interface to interact with the Elasticsearch management system
2. Create indices, add documents, and perform searches through the user-friendly UI
3. For advanced usage, interact directly with the FastAPI backend using the API documentation

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.