# SPDX-License-Identifier: AGPL-3.0-or-later """Plugin that displays an AI generated summary of the search query at the top of the result page. The summary is generated by a (local) LLM server that implements the `OpenAI chat completions API`_ -- e.g. `Ollama`_, vLLM, llama.cpp, LM Studio or Hugging Face TGI. The LLM server URL and the model are configured by the user in the *AI Summary* tab of the preferences (``ai_summary_server``, ``ai_summary_model``); the administrator can configure instance wide defaults in the ``ai_summary:`` section and lock the preferences via :ref:`settings preferences`. .. attention:: A user configurable server URL allows any user of the instance to make the SearXNG server send requests to a URL of their choice (`SSRF`_), and each summary is real LLM work. This plugin is intended for private instances -- on a public instance, lock the ``ai_summary_server``, ``ai_summary_model`` and ``ai_summary_grounding`` preferences and configure the ``ai_summary:`` section instead. The result page is never delayed by this plugin: it only places an empty placeholder (:py:obj:`searx.result_types.AiSummary`) in the answer area, which is filled asynchronously by the client (``client/simple/src/js/plugin/ AiSummary.ts``) from the ``/ai_summary`` endpoint (registered in :py:obj:`searx.webapp`). The endpoint re-emits the SSE token stream of the LLM server's ``/v1/chat/completions`` to the client as `NDJSON`_. A summary is only generated on the first page of a *general* search and only if no engine has contributed an infobox (e.g. wikipedia / wikidata) or an instant answer (e.g. ddg definitions) -- in these cases the query is most likely a lookup of a well known term that is already answered. The requests to the LLM server are sent directly (not via :py:obj:`searx.network`), an outgoing proxy configuration is deliberately not applied to reach an LLM server in the local network. Configuration of the defaults (:py:obj:`searx.ai_summary.SettingsAISummary`): .. code:: yaml ai_summary: base_url: "http://127.0.0.1:11434" model: "llama3.2:3b" .. code:: yaml plugins: searx.plugins.ai_summary.SXNGPlugin: active: false .. _Ollama: https://ollama.com/ .. _OpenAI chat completions API: https://platform.openai.com/docs/api-reference/chat .. _NDJSON: https://github.com/ndjson/ndjson-spec .. _SSRF: https://owasp.org/www-community/attacks/Server_Side_Request_Forgery """ import typing as t import json import logging import re import time from urllib.parse import urlparse import flask import httpx from flask_babel import gettext from searx import get_setting from searx.ai_summary import SettingsAISummary, build_chat_messages from searx.extended_types import sxng_request from searx.result_types import EngineResults import searx.ai_summary from . import Plugin, PluginInfo if t.TYPE_CHECKING: from searx.search import SearchWithPlugins from searx.extended_types import SXNG_Request from . import PluginCfg VALID_ROLES = ("user", "assistant") MODEL_NAME_REGEXP = re.compile(r"[A-Za-z0-9._:/-]{1,128}") def _get_client(base_url: str, cfg: SettingsAISummary) -> httpx.Client: """HTTP client for one request to the LLM server at ``base_url``.""" # the OpenAI API paths are prefixed with /v1, unless the base URL already # points into an API prefix base_url = base_url.rstrip("/") if not base_url.endswith("/v1"): base_url += "/v1" return httpx.Client( base_url=base_url, timeout=httpx.Timeout(connect=cfg.connect_timeout, read=cfg.read_timeout, write=10.0, pool=10.0), ) def _valid_server(url: str) -> bool: try: parsed = urlparse(url) except ValueError: return False return parsed.scheme in ("http", "https") and bool(parsed.netloc) and len(url) <= 256 def _user_server(request: "SXNG_Request", cfg: SettingsAISummary) -> str: """The LLM server URL for this request: the user's ``ai_summary_server`` preference, or the administrator's default.""" return str(request.preferences.get_value("ai_summary_server") or "").strip() or cfg.base_url class SXNGPlugin(Plugin): """Plugin that adds the AI summary placeholder to the result page, the ``/ai_summary`` endpoint itself is registered in :py:obj:`searx.webapp`.""" id = "ai_summary" def __init__(self, plg_cfg: "PluginCfg"): super().__init__(plg_cfg) self.info = PluginInfo( id=self.id, name=gettext("AI summary"), description=gettext( "Show an AI generated summary of the search query on top of the" " result page (uses a local LLM server, see the settings below)." ), preference_section="ai", ) def init(self, app: "flask.Flask") -> bool: cfg: SettingsAISummary = get_setting("ai_summary") if cfg.base_url: searx.ai_summary.MODELS = list(cfg.models) or self._probe_models(cfg) if not cfg.model and searx.ai_summary.MODELS: cfg.model = searx.ai_summary.MODELS[0] if cfg.model and cfg.model not in searx.ai_summary.MODELS: searx.ai_summary.MODELS.insert(0, cfg.model) return True def _probe_models(self, cfg: SettingsAISummary) -> list[str]: """Request the list of models from the LLM server (``GET /v1/models``). The server might not be up when SearXNG starts, a failing probe only leaves the model suggestion list empty.""" try: with _get_client(cfg.base_url, cfg) as client: resp = client.get("/models") resp.raise_for_status() models = [model["id"] for model in resp.json().get("data", [])] except (httpx.HTTPError, ValueError, KeyError) as exc: self.log.warning("can't request model list from %s: %s", cfg.base_url, exc) models = [] return models or ([cfg.model] if cfg.model else []) def post_search(self, request: "SXNG_Request", search: "SearchWithPlugins") -> EngineResults | None: results = EngineResults() sq = search.search_query cfg: SettingsAISummary = get_setting("ai_summary") skip = ( sq.pageno > 1 # post_search is also called for the json, csv and rss formats, # the placeholder is only useful on the HTML result page or request.form.get("format", "html") != "html" or "general" not in sq.categories # an infobox (e.g. wikipedia / wikidata) or an instant answer # (e.g. ddg definitions) most likely already answers the query or bool(search.result_container.infoboxes) or bool(search.result_container.answers) or not sq.query.strip() # without an LLM server (user preference or admin default) # there is nothing to show or not _user_server(request, cfg) ) if skip: return None grounding = bool(request.preferences.get_value("ai_summary_grounding")) results.add(results.types.AiSummary(query=sq.query, grounding=grounding)) return results def _bad_request(msg: str) -> flask.Response: return flask.Response(json.dumps({"error": msg}), status=400, mimetype="application/json") def _validate_messages(messages: t.Any, cfg: SettingsAISummary) -> list[dict[str, str]]: if not isinstance(messages, list) or not messages or len(messages) > cfg.max_history_messages: raise ValueError("invalid messages") for msg in messages: if not isinstance(msg, dict) or msg.keys() != {"role", "content"}: raise ValueError("invalid message") if msg["role"] not in VALID_ROLES or not isinstance(msg["content"], str): raise ValueError("invalid message") if not msg["content"].strip() or len(msg["content"]) > cfg.max_message_length: raise ValueError("invalid message") if messages[-1]["role"] != "user": raise ValueError("last message is not a user message") return messages def _validate_context(context: t.Any, cfg: SettingsAISummary) -> list[dict[str, str]]: if not isinstance(context, list) or len(context) > cfg.max_context_items: raise ValueError("invalid context") for item in context: if not isinstance(item, dict) or not item.keys() <= {"title", "url", "snippet"}: raise ValueError("invalid context item") for val in item.values(): if not isinstance(val, str) or len(val) > cfg.max_message_length: raise ValueError("invalid context item") return context def _validate_payload(payload: t.Any, cfg: SettingsAISummary) -> tuple[list[dict[str, str]], list[dict[str, str]]]: """Validate the request body of the ``/ai_summary`` endpoint and return the ``messages`` and ``context`` lists. Raises a :py:obj:`ValueError` for any malformed payload.""" if not isinstance(payload, dict): raise ValueError("payload is not an object") return _validate_messages(payload.get("messages"), cfg), _validate_context(payload.get("context", []), cfg) def ai_summary_view() -> flask.Response: """Stream an AI generated answer for the messages in the request body, response is NDJSON: ``{"delta": ..}`` lines followed by one final ``{"done": true, ..}`` line.""" cfg: SettingsAISummary = get_setting("ai_summary") if SXNGPlugin.id not in sxng_request.user_plugins: return flask.Response(json.dumps({"error": "plugin is not enabled"}), status=403, mimetype="application/json") try: messages, context = _validate_payload(sxng_request.get_json(force=True, silent=True), cfg) except ValueError as exc: return _bad_request(str(exc)) server = _user_server(sxng_request, cfg) if not _valid_server(server): return _bad_request("no valid LLM server configured") model = str(sxng_request.preferences.get_value("ai_summary_model") or "").strip() or cfg.model if not MODEL_NAME_REGEXP.fullmatch(model): return _bad_request("no valid model configured") chat_payload = { "model": model, "messages": build_chat_messages(cfg, messages, context), "stream": True, } # open the upstream connection before streaming, a connection error is # reported as HTTP 502 instead of a line in an already started stream client = _get_client(server, cfg) stream_ctx = client.stream("POST", "/chat/completions", json=chat_payload) upstream = None try: upstream = stream_ctx.__enter__() # pylint: disable=unnecessary-dunder-call if upstream.status_code != 200: stream_ctx.__exit__(None, None, None) upstream = None except httpx.HTTPError: upstream = None if upstream is None: client.close() return flask.Response(json.dumps({"error": "upstream error"}), status=502, mimetype="application/json") # from here on nothing must be read from the request context, the # generator runs after the request context has been torn down log = logging.getLogger("searx.plugins.ai_summary") def ndjson(obj: dict[str, t.Any]) -> bytes: # the generator bypasses flask's response encoding (direct_passthrough) return (json.dumps(obj) + "\n").encode() def generate(): start = time.monotonic() try: # the upstream is a SSE stream: "data: {..}" lines, terminated by # a "data: [DONE]" line for line in upstream.iter_lines(): if time.monotonic() - start > cfg.stream_timeout: yield ndjson({"done": True, "error": "timeout"}) return line = line.strip() if not line or line.startswith(":") or not line.startswith("data:"): continue payload = line[len("data:") :].strip() if payload == "[DONE]": break data = json.loads(payload) choices = data.get("choices") or [{}] delta = choices[0].get("delta", {}).get("content") or "" if delta: yield ndjson({"delta": delta}) yield ndjson({"done": True, "model": model}) except (httpx.HTTPError, ValueError) as exc: log.warning("error while streaming from the LLM server: %s", exc) yield ndjson({"done": True, "error": "upstream error"}) finally: stream_ctx.__exit__(None, None, None) client.close() return flask.Response( generate(), mimetype="application/x-ndjson", headers={"Cache-Control": "no-store", "X-Accel-Buffering": "no"}, direct_passthrough=True, )