MiniSearch is a self-hosted search engine with an AI assistant.
The AI can run entirely inside your browser tab, on GPU or CPU, so a working setup needs no API key, no separate inference server, and no third party seeing your queries. Web results come from a bundled SearXNG metasearch instance, are reranked locally, and the whole thing ships as a single Docker container.
- Private by design. No tracking, no telemetry, no accounts. Search history, cached results, and chats are stored in your browser and never leave your machine.
- AI in your browser. Pick from 38 curated models (135M to 4B parameters) that run on WebGPU where available and on CPU elsewhere. Models are downloaded once and cached by the browser.
- Any backend you like. Connect an OpenAI-compatible API (Ollama, LM Studio, vLLM, llama.cpp server, or a hosted provider), use the crowdsourced AI Horde, or let the server proxy your own API without exposing its key.
- A real search pipeline. Text and image results aggregated by SearXNG, reranked locally by a cross-encoder model, cached, and rate-limited; all inside the container.
- Answers you can verify. Responses cite the sources they draw from, support follow-up questions with conversation memory, reveal the model's reasoning on demand, and can be read aloud.
- Local history and analytics. Fuzzy-searchable history with pinning and full-session restore, plus usage statistics and an activity heatmap. Retention is configurable, and storage stays in the browser.
- Fits your workflow. Set it as your browser's default search engine, trigger it from Raycast, embed it in your own pages, and optionally protect your instance with access keys.
Run the published image:
docker run -p 7860:7860 ghcr.io/felladrin/minisearch:mainThen open http://localhost:7860 and start searching.
Use Docker Compose
Add the service to your docker-compose.yml:
services:
minisearch:
image: ghcr.io/felladrin/minisearch:main
ports:
- "7860:7860"Build from source
git clone https://github.com/felladrin/MiniSearch.git
cd MiniSearch
docker compose -f docker-compose.production.yml up --buildHost it on Hugging Face
Duplicate the Space to get your own hosted instance, no server required. Environment variables can be set in the Space settings.
flowchart LR
subgraph browser [Your browser]
UI[Search UI]
LocalAI[In-browser model<br/>WebGPU or CPU]
Storage[(IndexedDB<br/>history and cache)]
end
subgraph container [Docker container]
Server[App server]
SearXNG[SearXNG<br/>metasearch]
Reranker[Reranker<br/>llama-server]
end
UI <--> Storage
UI -->|search| Server
Server --> SearXNG
SearXNG --> Web((Web))
Server --> Reranker
UI -.->|in-browser inference| LocalAI
UI -.->|remote inference, optional| RemoteAPI[OpenAI-compatible API<br/>or AI Horde]
Your query goes to the app server, which asks the bundled SearXNG instance to aggregate results from multiple search engines. The server reranks them with a small cross-encoder model before returning them, and the browser caches them locally. If the AI response is enabled, the assistant reads the top results and writes a cited answer, either with a model running in your browser or through the backend you configured. The full picture is in docs/overview.md.
Set these in a .env file (see .env.example) when using Docker Compose, or pass them with -e/--env-file to docker run:
| Variable | Purpose | Default |
|---|---|---|
ACCESS_KEYS |
Comma-separated keys that gate access to the instance | Unset (open access) |
ACCESS_KEY_TIMEOUT_HOURS |
How long a validated key stays cached in the browser | 24 |
WLLAMA_DEFAULT_MODEL_ID |
Default model for in-browser inference | qwen-3-0.6b |
DEFAULT_INFERENCE_TYPE |
Backend preselected in the UI: browser, openai, horde, or internal |
browser |
INTERNAL_OPENAI_COMPATIBLE_API_BASE_URL |
Base URL of a self-hosted API that the server proxies for its users | Unset (disabled) |
INTERNAL_OPENAI_COMPATIBLE_API_KEY |
Key for that API; never sent to clients | Unset |
INTERNAL_OPENAI_COMPATIBLE_API_MODEL |
Model served through that API | Auto-detected |
INTERNAL_OPENAI_COMPATIBLE_API_NAME |
Name shown for it in the UI | Internal API |
The full reference, including server options such as PORT and ALLOWED_HOSTS, is in docs/configuration.md.
How do I make it my browser's default search engine?
Add a custom search engine in your browser settings using the pattern http://localhost:7860/?q=%s, replacing the host with your instance's address. Your search term replaces %s.
How do I search from Raycast?
Add this Quicklink to Raycast, and edit it to point to your own instance if you have one.
Can I use my own models through an OpenAI-compatible API?
Yes. Open the menu, set "AI Processing Location" to Remote server (API), then fill in the base URL, and optionally an API key and a model name. If the model is left blank, it is picked from the ones the API lists.
Can others use my instance with my API key without seeing it?
Yes. Configure the INTERNAL_OPENAI_COMPATIBLE_API_* variables from the Configuration table and restart the container. A new option with the name you chose appears in the "AI Processing Location" menu, and the key stays on the server.
Contributions are welcome. To set up a development environment:
git clone https://github.com/felladrin/MiniSearch.git
cd MiniSearch
docker compose upThe development server runs at http://localhost:7860 with hot reload. Before opening a pull request, run the quality gate:
docker compose exec development-server npm run lintSee the Contributing Guidelines, Code of Conduct, and Security Policy. The codebase is documented for humans and AI agents alike: agents.md is the navigation hub, and docs/ covers the architecture in depth.
MiniSearch builds on the work of these projects:
| Project | Role |
|---|---|
| SearXNG | Metasearch engine behind the results |
| wllama and llama.cpp | In-browser inference and local reranking |
| AI Horde | Crowdsourced distributed inference |
| AI SDK | Client for OpenAI-compatible APIs |
| Mantine | UI components |
| Hugging Face | Model hosting and the live demo Space |
MiniSearch is released under the Apache License 2.0.