"""
AI Answers Plugin - Interactive Demo Server
Simulates SearXNG environment for local development and testing.
Usage: python demo.py
Then visit: http://localhost:5000/?q=your+query+here
Requires: pip install flask flask-babel python-dotenv
"""
import sys
import os
import logging
from types import ModuleType
from flask import Flask, request
from dotenv import load_dotenv
logging.basicConfig(level=logging.INFO, format='%(levelname)s: %(message)s')
load_dotenv()
os.environ.setdefault('LLM_STYLE', 'interactive')
# Mock SearXNG modules
searx = ModuleType("searx")
searx_plugins = ModuleType("searx.plugins")
searx_results = ModuleType("searx.result_types")
class MockPlugin:
def __init__(self, cfg):
self.active = getattr(cfg, 'active', True)
class MockPluginInfo:
def __init__(self, **kwargs):
self.meta = kwargs
class MockEngineResults:
def __init__(self):
self.types = ModuleType("types")
self.types.Answer = lambda *args, **kwargs: kwargs.get('answer', args[0] if args else "")
self._results = []
def add(self, res):
self._results.append(res)
searx_plugins.Plugin = MockPlugin
searx_plugins.PluginInfo = MockPluginInfo
searx_results.EngineResults = MockEngineResults
sys.modules["searx"] = searx
sys.modules["searx.plugins"] = searx_plugins
sys.modules["searx.result_types"] = searx_results
from ai_answers import SXNGPlugin
from flask_babel import Babel
app = Flask(__name__)
babel = Babel(app)
class MockConfig:
active = True
plugin = SXNGPlugin(MockConfig())
plugin.init(app)
@app.route("/")
def index():
query = request.args.get("q", "why is the sky blue")
class MockSearchQuery:
pageno = 1
lang = 'en'
categories = ['general']
MockSearchQuery.query = query
class MockSearch:
search_query = MockSearchQuery()
class MockResultContainer:
def __init__(self):
self.answers = set()
def get_ordered_results(self):
if 'quantum' in query.lower():
return [
{"title": "IBM Quantum", "content": "Quantum computers rely on qubits, which can represent 0, 1, or both via superposition. They solve complex problems faster.", "url": "https://www.ibm.com/quantum", "publishedDate": "2026-01-15"},
{"title": "Nature Physics", "content": "Entanglement allows qubits to be correlated instantly across distances. This is key for quantum cryptography and teleportation.", "url": "https://nature.com/articles/quantum", "publishedDate": "2026-01-10"},
{"title": "Wikipedia", "content": "Quantum computing uses quantum mechanics. Major applications include drug discovery and materials science.", "url": "https://en.wikipedia.org/wiki/Quantum_computing", "publishedDate": "2025-12-01"}
]
return [
{"title": "Wikipedia", "content": "The sky appears blue due to Rayleigh scattering of sunlight.", "url": "https://en.wikipedia.org/wiki/Rayleigh_scattering", "publishedDate": "2026-01-15"},
{"title": "NASA Science", "content": "Shorter blue wavelengths scatter more than longer red wavelengths.", "url": "https://science.nasa.gov/blue-sky", "publishedDate": "2026-01-10"},
{"title": "Physics Today", "content": "The atmosphere acts as a filter, scattering blue light in all directions.", "url": "https://physicstoday.org/atmosphere", "publishedDate": "2026-01-01"}
]
result_container = MockResultContainer()
search = MockSearch()
plugin.post_search(None, search)
injection_html = ""
if search.result_container.answers:
injection_html = list(search.result_container.answers)[0]
return f"""
AI Answers Demo
Provider: {plugin.provider or 'Not configured'} | Model: {plugin.model or 'N/A'}
Query: {query}
{injection_html if injection_html else 'Plugin inactive. Set LLM_PROVIDER and LLM_KEY in .env
'}
Try: /?q=what+is+quantum+computing
"""
if __name__ == "__main__":
print()
print("=" * 50)
print(" AI Answers Plugin - Demo Server")
print("=" * 50)
print(f" Provider: {plugin.provider or 'NOT SET'}")
print(f" Model: {plugin.model or 'N/A'}")
print(f" Style: {plugin.style}")
print(f" Status: {'Active' if plugin.api_key else 'Inactive (no LLM_KEY)'}")
print("=" * 50)
print(" http://localhost:5000/?q=your+query+here")
print("=" * 50)
print()
app.run(debug=True, port=5000)