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https://github.com/felladrin/MiniSearch

Minimalist web-searching app with an AI assistant that runs directly from your browser. Uses Web-LLM, Ratchet-ML, Wllama and SearXNG. Demo: https://felladrin-minisearch.hf.space
https://github.com/felladrin/MiniSearch

ai artificial-intelligence generative-ai gpu-accelerated information-retrieval llm llm-inference machine-learning nlp question-answering ratchet-ml retrieval-augmented-generation search search-engine searxng typescript web-llm webapp wllama

Last synced: 3 months ago
JSON representation

Minimalist web-searching app with an AI assistant that runs directly from your browser. Uses Web-LLM, Ratchet-ML, Wllama and SearXNG. Demo: https://felladrin-minisearch.hf.space

Host: GitHub
URL: https://github.com/felladrin/MiniSearch
Owner: felladrin
License: apache-2.0
Created: 2023-10-14T12:23:56.000Z (about 1 year ago)
Default Branch: main
Last Pushed: 2024-05-28T18:05:40.000Z (8 months ago)
Last Synced: 2024-05-29T05:55:43.845Z (8 months ago)
Topics: ai, artificial-intelligence, generative-ai, gpu-accelerated, information-retrieval, llm, llm-inference, machine-learning, nlp, question-answering, ratchet-ml, retrieval-augmented-generation, search, search-engine, searxng, typescript, web-llm, webapp, wllama
Language: TypeScript
Homepage: https://felladrin-minisearch.hf.space
Size: 25.1 MB
Stars: 76
Watchers: 3
Forks: 9
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: license.txt

Awesome Lists containing this project

StarryDivineSky - felladrin/MiniSearch
awesome-repositories - felladrin/MiniSearch - Minimalist web-searching platform with an AI assistant that runs directly from your browser. Uses WebLLM, Wllama and SearXNG. Demo: https://felladrin-minisearch.hf.space (TypeScript)

README

# MiniSearch

A minimalist web-searching app with an AI assistant that runs directly from your browser.

Live demo: https://felladrin-minisearch.hf.space

## Screenshot

![MiniSearch Screenshot](https://github.com/user-attachments/assets/f8d72a8e-a725-42e9-9358-e6ebade2acb2)

## Features

- **Privacy-focused**: [No tracking, no ads, no data collection](https://docs.searxng.org/own-instance.html#how-does-searxng-protect-privacy)
- **Easy to use**: Minimalist yet intuitive interface for all users
- **Cross-platform**: Models run inside the browser, both on desktop and mobile
- **Integrated**: Search from the browser address bar by setting it as the default search engine
- **Efficient**: Models are loaded and cached only when needed
- **Customizable**: Tweakable settings for search results and text generation
- **Open-source**: [The code is available for inspection and contribution at GitHub](https://github.com/felladrin/MiniSearch)

## Prerequisites

- [Docker](https://docs.docker.com/get-docker/)

## Getting started

There are two ways to get started with MiniSearch. Pick one that suits you best.

**Option 1** - Use [MiniSearch's Docker Image](https://github.com/felladrin/MiniSearch/pkgs/container/minisearch) by running:

```bash
docker run -p 7860:7860 ghcr.io/felladrin/minisearch:main
```

**Option 2** - Build from source by [downloading the repository files](https://github.com/felladrin/MiniSearch/archive/refs/heads/main.zip) and running:

```bash
docker compose -f docker-compose.production.yml up --build
```

Then, open http://localhost:7860 in your browser and start searching!

## Frequently asked questions

How do I search via the browser's address bar?

You can set MiniSearch as your browser's address-bar search engine using the pattern http://localhost:7860/?q=%s, in which your search term replaces %s.

Can I use custom models via OpenAI-Compatible API?

Yes! For this, open the Menu and change the "AI Processing Location" to Remote server (API). Then configure the Base URL, and optionally set an API Key and a Model to use.

How do I restrict the access to my MiniSearch instance via password?

Create a .env file and set a value for ACCESS_KEYS. Then reset the MiniSearch docker container.

For example, if you to set the password to PepperoniPizza, then this is what you should add to your .env:

ACCESS_KEYS="PepperoniPizza"

You can find more examples in the .env.example file.

I want to serve MiniSearch to other users, allowing them to use my own OpenAI-Compatible API key, but without revealing it to them. Is it possible?

Yes! In MiniSearch, we call this text-generation feature "Internal OpenAI-Compatible API". To use this it:

Set up your OpenAI-Compatible API endpoint by configuring the following environment variables in your .env file:
- INTERNAL_OPENAI_COMPATIBLE_API_BASE_URL: The base URL for your API
- INTERNAL_OPENAI_COMPATIBLE_API_KEY: Your API access key
- INTERNAL_OPENAI_COMPATIBLE_API_MODEL: The model to use
- INTERNAL_OPENAI_COMPATIBLE_API_NAME: The name to display in the UI

Restart MiniSearch server.

In the MiniSearch menu, select the new option (named as per your INTERNAL_OPENAI_COMPATIBLE_API_NAME setting) from the "AI Processing Location" dropdown.

How can I contribute to the development of this tool?

Fork this repository and clone it. Then, start the development server by running the following command:

docker compose up

Make your changes, push them to your fork, and open a pull request! All contributions are welcome!

Why is MiniSearch built upon SearXNG's Docker Image and using a single image instead of composing it from multiple services?

There are a few reasons for this:

MiniSearch utilizes SearXNG as its meta-search engine.

Manual installation of SearXNG is not trivial, so we use the docker image they provide, which has everything set up.

SearXNG only provides a Docker Image based on Alpine Linux.

The user of the image needs to be customized in a specific way to run on HuggingFace Spaces, where MiniSearch's demo runs.

HuggingFace only accepts a single docker image. It doesn't run docker compose or multiple images, unfortunately.