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https://github.com/breadrock1/doc-searcher
There is simple documents searcher project based on Rust and Elasticsearch technologies.
https://github.com/breadrock1/doc-searcher
arctic documents elasticsearch fulltext-search nosql rest-api rust search ssdeep
Last synced: 3 days ago
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There is simple documents searcher project based on Rust and Elasticsearch technologies.
- Host: GitHub
- URL: https://github.com/breadrock1/doc-searcher
- Owner: breadrock1
- Created: 2023-09-28T07:28:57.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2024-10-27T22:37:33.000Z (18 days ago)
- Last Synced: 2024-10-28T02:50:23.638Z (18 days ago)
- Topics: arctic, documents, elasticsearch, fulltext-search, nosql, rest-api, rust, search, ssdeep
- Language: Rust
- Homepage:
- Size: 1010 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
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# Doc-Searcher
Doc-Searcher is a simple and flexible document search application, leveraging the capabilities of Rust and Elasticsearch (by default)
to provide efficient and effective full-text search in documents. This project aims to offer a straightforward solution for
indexing and searching through a large corpus of documents with the speed and accuracy provided by Elasticsearch.
The main goal - implement simple but powerful system of storing and indexing documents with searching functionality (full-text, semantic).
I decided to use elasticsearch as default searching engine, but you may use own solutions by implementing several async traits
for Tantivy, QDrant or own solution:
- CacherService - API of doc-notifier service interactions;
- EmbeddingsService - API of doc-notifier service interactions;
- MetricsService - API of metrics to monitoring;
- StorageService - API (CRUD) of indexed folders and documents;
- SearcherService - API of searcher functionalities (fulltext, vector, similar).
## Features
- **Full-Text Search**: Quickly find documents based on content based on choose searching engine;
- **Semantic Search**: Fast semantic searching by external embeddings service;
- **Rust Performance**: Benefit from the speed and safety of Rust;
- **REST API**: Easy to use REST API for searching documents and control management of indexing;
- **Docker Support**: Easy deployment with Docker and docker-compose;
- **Caching Actor**: Store data to cache service like Redis or own solutions;
- **Remote logging**: Send error or warning messages or other metrics to remote server;
- **Swagger**: Using swagger documentation service for all available endpoints;
- **Cors Origins**: Allows to provide web pages with access to resources of another domain;
- **Parsing and storing**: Allows to parse and store files to searching engine localy.
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
### Prerequisites
- Rust
- Docker & docker-compose
- Cache (Redis)
- Elasticsearch
### Installation
1. Clone the repository
2. Run `cargo install --path .` to build project
3. Setting up `.env` file with services creds
4. Run `cargo run --bin doc-searcher-init` to init elasticsearch schemas
4. Run `cargo run --bin doc-searcher-run` to launch service
### Features of project
Features to parse and store documents localy from current service (Not stable):
- enable-cacher - enable cacher service like redis oe other custom implementation;
- enable-semantic - enable llm service for semantic searching.
[](https://github.com/breadrock1/doc-searcher)
[](https://github.com/breadrock1/doc-searcher)
[](https://github.com/breadrock1/doc-searcher)