MiniSearch

About

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.

Features

• 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 several 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.

Quick start

Run the published image:

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

Then open http://localhost:7860 and start searching.

latest moves on every release, so it changes under you. To stay on a known-good build, pin the digest, which always identifies the same image:

docker inspect --format '{{index .RepoDigests 0}}' ghcr.io/felladrin/minisearch:latest
docker run -p 7860:7860 ghcr.io/felladrin/minisearch@sha256:1a2b3c...

The version the running instance reports (in the menu, and under build on /status) tells you which commit it was built from.

Images carry provenance and SBOM attestations, which you can inspect with:

docker buildx imagetools inspect ghcr.io/felladrin/minisearch:latest

Add the service to your docker-compose.yml:

services:
  minisearch:
    image: ghcr.io/felladrin/minisearch:latest
    ports:
      - "7860:7860"

git clone https://github.com/felladrin/MiniSearch.git
cd MiniSearch
docker compose -f docker-compose.production.yml up --build

Duplicate the Space to get your own hosted instance, no server required. Environment variables can be set in the Space settings.

How it works

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/>ONNX Runtime]
    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.

Configuration

MiniSearch works out-of-the-box, but you can customize it if you want. More details at docs/configuration.md.

FAQ

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.

Add this Quicklink to Raycast, and edit it to point to your own instance if you have one.

Yes. Open the menu, set "AI Processing Location" to Remote server (OpenAI-compatible 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.

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.

Contributing

See the Contributing Guidelines, Code of Conduct, and Security Policy.

Releases

Each release is cut with a CalVer tag (YYYY.M.D). Notable changes are documented in the Changelog.

License

Apache License 2.0