searxng/docs/dev/plugins/ai_summary.rst

.. _ai_summary plugin:

==========
AI Summary
==========

.. sidebar:: Further reading ..

   - :ref:`Configuration <settings ai_summary>`
   - :ref:`dev plugin`
   - :ref:`result types`

The AI Summary plugin shows a generated answer above the ordinary search
results, unless an engine has already answered the query directly -- with a
Wikipedia infobox, for instance, or an instant answer.  It is meant to run
against a local LLM server and speaks the `OpenAI chat completions API`_, so it
works with `Ollama`_, Hugging Face TGI, LiteLLM, vLLM, llama.cpp and anything
else that implements that specification.  See :ref:`its configuration <settings
ai_summary>` for how to set one up.

The purpose of the summary is not to tell you what the model memorised during
training, but to summarise the up to date results your query actually returned.
That is what the *grounding* setting does, and why it is enabled by default.

Generating an answer takes seconds, and a search engine that waits seconds
before painting anything is a broken search engine.  The summary is therefore
produced asynchronously: the plugin renders an empty box, the result page is
delivered immediately, and the browser fills that box from a second, streaming
request.  The results below stay readable and scrollable the whole time.


Request flow
============

.. _ai_summary dataflow:

.. kernel-render:: DOT
   :alt: Data flow between browser, SearXNG and the LLM server
   :caption: A search that produces a summary: two requests, not one

   digraph ai_summary {
     rankdir=LR;
     graph [fontname="sans-serif", ranksep=1.1, nodesep=0.4];
     node  [fontname="sans-serif", fontsize=11, shape=box, style="rounded,filled",
            fillcolor="#f4f4f4", color="#999999"];
     edge  [fontname="sans-serif", fontsize=9, color="#666666"];

     browser  [label="browser\n(simple theme)"];
     searxng  [label="SearXNG"];
     engines  [label="search engines", fillcolor="#ffffff"];
     llm      [label="LLM server\nOllama, vLLM, ...", fillcolor="#ffffff"];

     browser -> searxng [label=" 1  GET /search"];
     searxng -> engines [label=" 2  query"];
     searxng -> browser [label=" 3  result page,\l    empty summary box\l", constraint=false];
     browser -> searxng [label=" 4  POST /ai_summary\l    (query + results)\l"];
     searxng -> llm     [label=" 5  POST /v1/chat/completions"];
     llm     -> searxng [label=" 6  SSE token stream", constraint=false];
     searxng -> browser [label=" 7  NDJSON token stream", constraint=false];
   }

Steps 1--3 are an ordinary SearXNG search.  The plugin's
:py:obj:`post_search <searx.plugins.ai_summary.SXNGPlugin.post_search>` hook
adds an empty :py:obj:`searx.result_types.AiSummary` placeholder to the answer
area and returns immediately, so the page is not delayed.

Steps 4--7 happen in the browser after the page has painted.
``client/simple/src/js/plugin/AiSummary.ts`` posts to the ``/ai_summary``
endpoint, which opens a streaming request to the LLM server and re-emits the
tokens as they arrive.  The user sees the answer being written.

Two format changes happen along the way.  The LLM server speaks `SSE`_
(``data: {...}`` lines, terminated by ``data: [DONE]``), because that is what
the OpenAI chat completions API specifies.  SearXNG re-emits that to the
browser as `NDJSON`_ -- one JSON object per line, ``{"delta": "..."}`` for each
chunk of text and a final ``{"done": true}``.  NDJSON is used because the
browser reads the body with ``fetch`` and a stream reader, where SSE's
``EventSource`` would be the wrong tool: ``EventSource`` cannot issue a POST.


When no summary is generated
============================

:py:obj:`post_search <searx.plugins.ai_summary.SXNGPlugin.post_search>` skips
the placeholder entirely for:

- page two and beyond -- a summary belongs with the first impression of a query
- anything but the *general* category
- non-HTML output formats (the JSON, CSV and RSS APIs)
- queries where an engine already produced an infobox (wikipedia, wikidata) or
  an instant answer (e.g. ddg definitions)
- an empty query, or no LLM server configured

The infobox rule mirrors what the big engines do: if the query is a lookup of a
well known entity, that entity's own data is a better answer than a generated
paragraph.


Where the API key goes
======================

The administrator's ``api_key`` is only ever sent to the administrator's
``base_url``.  This matters because users may set their own server in the
``ai_summary_server`` preference: without the check, any user of the instance
could point that preference at a host they control and collect the instance's
key from the ``Authorization`` header.  Users authenticate to their own server
with their own ``ai_summary_api_key`` preference, which is stored in a cookie
and deliberately excluded from the shareable preferences URL.

:py:obj:`_server_api_key <searx.plugins.ai_summary._server_api_key>` implements
the rule; a URL carrying credentials in its userinfo is rejected outright,
because HTTP clients turn that into an ``Authorization`` header of the user's
choosing.


Implementation notes
====================

The ``/ai_summary`` route is registered in :py:obj:`searx.webapp`, next to the
favicon proxy, rather than in the plugin's ``init()``.  Flask does not allow
``add_url_rule`` after the first request has been handled, and registering it
from a plugin breaks the test suite.

Requests to the LLM server bypass :py:obj:`searx.network` and are sent with a
plain :py:obj:`httpx.Client`.  The outgoing proxy configuration is deliberately
not applied: an LLM server usually sits on localhost or in the local network,
which is exactly what an outgoing proxy is configured to avoid.

The streaming response uses ``direct_passthrough``, so the generator must yield
``bytes`` -- werkzeug asserts on ``str``, and the Flask test client does not
catch it.

.. _Ollama: https://ollama.com/
.. _OpenAI chat completions API: https://platform.openai.com/docs/api-reference/chat
.. _SSE: https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events
.. _NDJSON: https://github.com/ndjson/ndjson-spec

Reference
=========

.. automodule:: searx.plugins.ai_summary
   :members: