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[doc] ai_summary: describe the plugin, not the reasoning behind it

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Both pages carried design rationale and implementation notes that belong
in a review conversation rather than in documentation: why NDJSON is
sent to the browser instead of SSE, why the endpoint is registered in
webapp.py, why the outgoing proxy is bypassed. They are gone, along with
the troubleshooting section.

The section about public instances no longer opens by saying the plugin
is meant for private instances, which contradicted the instructions that
followed it. It now explains why the server, model and key are user
preferences at all -- so that they can be changed at home without
editing settings.yml -- and what that means once other people can reach
the instance.

"AI Summary" is the plugin, "AI summary" is the text it produces, and an
"instance" is always a SearXNG one; a page that also talks about LLM
servers cannot leave that to context.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
This commit is contained in:
jasonwitty
2026-08-13 16:11:49 -07:00
parent 054b3a5c0d
commit 37d7d11959
2 changed files with 85 additions and 175 deletions
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docs/admin/settings/settings_ai_summary.rst
+47 -98
View File
@@ -13,11 +13,10 @@
Configuration of the :ref:`AI Summary plugin <ai_summary plugin>`, which shows a
short AI generated answer above the search results.
The text is produced by an **LLM server that you run** -- SearXNG does not ship
a model and does not talk to any AI provider on its own. Anything that speaks
the `OpenAI chat completions API`_ works: `Ollama`_, vLLM, llama.cpp, LM Studio,
Hugging Face TGI and others. The plugin is not activated by default.
The text is produced by an LLM server that you run; SearXNG ships no model and
contacts no AI provider of its own. Any server implementing the `OpenAI chat
completions API`_ works: `Ollama`_, vLLM, llama.cpp, LM Studio, Hugging Face
TGI and others. The plugin is not activated by default.
.. _ai_summary quickstart:
@@ -39,8 +38,8 @@ A local setup on the same machine as SearXNG, in four steps.
ollama pull gemma3:4b
``gemma3:4b`` needs roughly 4 GB of memory and runs on CPU if you have no GPU.
On a small machine use ``gemma3:1b`` instead; any model in the `Ollama
library`_ works.
On a smaller machine use ``gemma3:1b``; any model in the `Ollama library`_
works.
**3. Configure SearXNG**
@@ -71,20 +70,18 @@ Add this to your ``settings.yml``:
.. warning::
A ``plugins:`` block **replaces** the default list, it is not merged into it
(:ref:`settings plugins`). If you list only the AI Summary plugin, every
other plugin is switched off. That is why the block above repeats the
defaults -- drop the lines for plugins you do not want.
(:ref:`settings plugins`). Listing only the AI Summary plugin switches
every other plugin off, which is why the block above repeats the defaults --
drop the lines for plugins you do not want.
**4. Restart SearXNG** and search for something.
The summary appears above the results while it is still being written. If
nothing appears, see :ref:`ai_summary troubleshooting`.
The summary appears above the results while it is still being written.
Options
=======
Only ``base_url`` is required; a model is needed too, but if you leave ``model``
Only ``base_url`` is required. A model is needed too, but if ``model`` is left
empty the first entry of ``models`` is used.
.. code:: yaml
@@ -97,13 +94,12 @@ empty the first entry of ``models`` is used.
.. autoclass:: searx.ai_summary.SettingsAISummary
:members:
Servers that require authentication
===================================
Servers that need a password
============================
Some servers require authentication -- vLLM and llama.cpp when started with
``--api-key``, a gateway such as LiteLLM, or any LLM server placed behind an
authenticating reverse proxy. Give SearXNG the key with ``api_key``:
vLLM and llama.cpp started with ``--api-key``, a gateway such as LiteLLM, or an
LLM server behind an authenticating reverse proxy all expect a key. Set it
with ``api_key``:
.. code:: yaml
@@ -112,59 +108,47 @@ authenticating reverse proxy. Give SearXNG the key with ``api_key``:
api_key: "sk-..."
model: "gemma3:4b"
The key is sent as an ``Authorization: Bearer`` header, and only to the server
in ``base_url``. Users who point the ``ai_summary_server`` preference at a
server of their own never receive it; they set their own key in the
``ai_summary_api_key`` preference instead.
SearXNG has no separate secret store, so the key sits in ``settings.yml`` --
make sure that file is readable only by the user SearXNG runs as.
The key is sent as an ``Authorization: Bearer`` header and only to the server in
``base_url``. Users who configure a server of their own in the
``ai_summary_server`` preference never receive it; they set their own key in the
``ai_summary_api_key`` preference.
SearXNG has no separate secret store, so the key is held in ``settings.yml`` --
that file should be readable only by the user SearXNG runs as.
.. _ai_summary grounding:
Grounding
=========
Grounding decides *what the model is told*:
With ``grounding`` enabled, which is the default, the query **and the top search
results** (title, URL and snippet, at most ``max_context_items`` of them) are
sent to the LLM server, and the answer reflects what the search found. With it
disabled only the query is sent and the model answers from its training data.
Users can change this in the ``ai_summary_grounding`` preference.
``grounding: true`` (the default)
The query **and the top search results** (title, URL and snippet, at most
``max_context_items`` of them) are sent to the LLM server. Answers reflect
what the search actually found, so they are more accurate and more current.
What leaves the network therefore depends on where the LLM server runs: with a
server on localhost or in the local network, nothing does.
``grounding: false``
Only the query is sent, and the model answers from its own training data.
Faster and cheaper, but the answer can be outdated or invented.
Public SearXNG instances
========================
Users can switch this in their preferences (``ai_summary_grounding``).
The server URL, model and API key are user preferences so that someone running
SearXNG at home can switch models or debug their LLM server from the
preferences page, without editing ``settings.yml`` and restarting.
How much this matters for privacy depends entirely on where the LLM server runs.
With a server on localhost or in your own network, nothing leaves that network.
With a hosted server, the query and the result snippets are sent to the
provider. This is the main reason a local server is recommended.
Public instances
================
On public SearXNG instances, those same preferences let any visitor choose the
address the summary request is sent to. The request is made by the SearXNG
host, so a visitor can use it to reach machines on your network that they have
no route to themselves -- an `SSRF`_ vector.
.. attention::
The plugin is designed for private instances. Read this before enabling it
on a public one.
Lock ``ai_summary_server`` on any SearXNG instance that is reachable by
people outside your household.
Two things change on a public instance:
**Every search costs real work.** A summary is a full LLM inference. Traffic
that was cheap to serve becomes expensive, on hardware you pay for.
**Users can choose the server SearXNG talks to.** The ``ai_summary_server``
preference makes your instance send requests to an address of the user's
choosing, which is a `SSRF`_ vector: it can be pointed at services inside your
network that are not reachable from outside.
Lock the preferences so that only your configuration is used
(:ref:`settings preferences`):
Locking a preference makes SearXNG use your configured value and ignore the
user's (:ref:`settings preferences`):
.. code:: yaml
@@ -175,46 +159,11 @@ Lock the preferences so that only your configuration is used
- ai_summary_model
- ai_summary_grounding
Locking ``ai_summary_server`` closes the SSRF vector; locking
``ai_summary_api_key`` stops users making your instance send an
``Authorization`` header of their choosing to a host of their choosing.
.. _ai_summary troubleshooting:
Troubleshooting
===============
**No summary appears at all.**
The plugin deliberately stays quiet in several cases: on page two and beyond,
outside the *general* category, and when an engine already answered the query
with an infobox or an instant answer. Try a question-like query on the first
page. Check that the plugin is enabled both in ``settings.yml`` and in your
own preferences.
**The model list in the preferences is empty.**
SearXNG asks the server for its models (``GET /v1/models``) once at startup.
An empty list means that request failed -- the server was not running yet,
the URL is wrong, or it needs an ``api_key``. The log records the reason;
restart SearXNG after fixing it.
**The summary box shows an error.**
SearXNG could not reach the LLM server, or the server rejected the request.
Check ``base_url`` from the SearXNG machine, confirm the model name exists on
that server (``ollama list``), and check the SearXNG log -- it records the
status and the message the server replied with, which usually names the cause.
**The first search after a while fails, the next one works.**
An idle LLM server unloads the model and has to load it again, and it sends
nothing at all while doing so. If that takes longer than ``read_timeout``
(30 s by default) the request is abandoned. SearXNG repeats the request once,
which covers a normal load, but a large model on slow storage can need more:
raise ``read_timeout``, or keep the model in memory -- with Ollama, set
``OLLAMA_KEEP_ALIVE`` (for example ``-1`` to never unload it).
**The summary starts, then stops mid-sentence.**
The answer exceeded ``stream_timeout`` (120 s by default). Large models on
CPU are slow; either raise the limit or use a smaller model.
``ai_summary_server`` is the one that matters: locking it closes the SSRF
vector. Locking ``ai_summary_api_key`` additionally stops visitors making your
SearXNG instance send an ``Authorization`` header of their choosing to a host of
their choosing. ``ai_summary_model`` and ``ai_summary_grounding`` are about
cost and consistency rather than security.
.. _Ollama: https://ollama.com/
.. _Ollama library: https://ollama.com/library