AI Answers Plugin for SearXNG

Single file install
Does not block result loading time

A SearXNG plugin that generates AI answers using search results as RAG context. Supports 8+ LLM providers.

Features:

token-by-token UI streaming
clickable inline citations
interactive mode to continue summary, ask follow ups, copy, or regenerate
simple response mode with no extras

Installation

Place ai_answers.py into the searx/plugins directory of your instance (or mount it in a container) and enable it in settings.yml:

plugins:
  searx.plugins.ai_answers.SXNGPlugin:  
    active: true

Configuration

Set the following environment variables:

Required

LLM_PROVIDER: openrouter, openai, ollama, localai, lmstudio, gemini, azure, or huggingface
LLM_KEY: Your API key

Optional

LLM_MODEL: Model identifier. Defaults vary by provider.
LLM_URL: Custom endpoint URL. Overrides provider preset.
LLM_MAX_TOKENS: Defaults to 500.
LLM_TEMPERATURE: Defaults to 0.2.
LLM_CONTEXT_COUNT: Search results to include. Defaults to 5.
LLM_TABS: Comma-separated tab whitelist. Defaults to general,science,it,news.
LLM_STYLE: UI mode. Set to "simple" for no interactive controls (copy, regenerate, follow up, continue). Defaults to simple.

How It Works

After search completes, the plugin extracts top search results as context. A client-side script calls the stream endpoint with a signed token. The LLM response streams back token by token.

Examples

OpenRouter

LLM_PROVIDER=openrouter
LLM_KEY=sk-or-xxx
LLM_MODEL=google/gemma-3-27b-it:free

Ollama (Local)

LLM_PROVIDER=ollama
LLM_KEY=ollama
LLM_MODEL=llama3.2

LocalAI

LLM_PROVIDER=localai
LLM_KEY=your-key
LLM_MODEL=gpt-4
LLM_URL=http://localai.lan:8080/v1/chat/completions

Gemini

LLM_PROVIDER=gemini
LLM_KEY=AIzaSy...
LLM_MODEL=gemma-3-27b-it

Azure

LLM_PROVIDER=azure
LLM_KEY=your-api-key
LLM_URL=https://your-resource.openai.azure.com/openai/deployments/your-deployment/chat/completions?api-version=2024-02-01

Hugging Face

LLM_PROVIDER=huggingface
LLM_KEY=hf_xxx
LLM_MODEL=meta-llama/Meta-Llama-3-8B-Instruct

Development

pip install flask flask-babel python-dotenv
python demo.py   # Interactive test server on localhost:5000
python test.py   # One-shot test suite