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).

• 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.

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

• Rust
• Docker & docker-compose
• Cache (Redis)
• Elasticsearch

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
5. Run cargo run --bin doc-searcher-run to launch service

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.