import json, http.client, ssl, os, logging, base64 from flask import Response, request from searx.plugins import Plugin, PluginInfo from searx.result_types import EngineResults from flask_babel import gettext from markupsafe import Markup logger = logging.getLogger(__name__) class SXNGPlugin(Plugin): id = "gemini_flash" def __init__(self, plg_cfg): super().__init__(plg_cfg) self.info = PluginInfo( id=self.id, name=gettext("Gemini Flash Streaming"), description=gettext("Live AI search answers using Google Gemini Flash"), preference_section="general", ) self.api_key = os.getenv('GEMINI_API_KEY') self.model = os.getenv('GEMINI_MODEL', 'gemini-3-flash-preview') self.max_tokens = int(os.getenv('GEMINI_MAX_TOKENS', 500)) self.temperature = float(os.getenv('GEMINI_TEMPERATURE', 0.2)) def init(self, app): @app.route('/gemini-stream', methods=['POST']) def g_stream(): data = request.json or {} context_text = data.get('context', '') q = data.get('q', '') if not self.api_key or not q: return Response("Error: Missing Key or Query", status=400) def generate(): host = "generativelanguage.googleapis.com" path = f"/v1beta/models/{self.model}:streamGenerateContent?key={self.api_key}" try: conn = http.client.HTTPSConnection(host, context=ssl.create_default_context()) prompt = ( f"SYSTEM: Answer USER QUERY by integrating SEARCH RESULTS with expert knowledge.\n" f"HIERARCHY: Use RESULTS for facts/data. Use KNOWLEDGE for context/synthesis.\n" f"CONSTRAINTS: <4 sentences | Dense information | Complete thoughts.\n" f"FALLBACK: If results are empty, answer from knowledge but note the lack of sources.\n\n" f"SEARCH RESULTS:\n{context_text}\n\n" f"USER QUERY: {q}\n\n" f"ANSWER:" ) payload = {"contents": [{"parts": [{"text": prompt}]}], "generationConfig": {"maxOutputTokens": self.max_tokens, "temperature": self.temperature}} conn.request("POST", path, body=json.dumps(payload), headers={"Content-Type": "application/json"}) res = conn.getresponse() if res.status != 200: yield f" [Error: {res.status} {res.reason} - {res.read().decode('utf-8')}]" return decoder = json.JSONDecoder() buffer = "" for chunk in res: if not chunk: continue buffer += chunk.decode('utf-8') while buffer: buffer = buffer.lstrip() if not buffer: break try: obj, idx = decoder.raw_decode(buffer) candidates = obj.get('candidates', []) if candidates: content = candidates[0].get('content', {}) parts = content.get('parts', []) if parts: text = parts[0].get('text', '') if text: yield text buffer = buffer[idx:] except json.JSONDecodeError: break conn.close() except Exception as e: yield f" [Error: {str(e)}]" return Response(generate(), mimetype='text/plain', headers={'X-Accel-Buffering': 'no'}) return True def post_search(self, request, search) -> EngineResults: results = EngineResults() if not self.active or not self.api_key or search.search_query.pageno > 1: return results raw_results = search.result_container.get_ordered_results() context_list = [f"[{i+1}] {r.get('title')}: {r.get('content')}" for i, r in enumerate(raw_results[:6])] context_str = "\n".join(context_list) b64_context = base64.b64encode(context_str.encode('utf-8')).decode('utf-8') js_q = json.dumps(search.search_query.query) html_payload = f''' ''' search.result_container.answers.add(results.types.Answer(answer=Markup(html_payload))) return results