Files
searxng/searx/ai_summary.py
T
jasonwitty 19cc7a6f9f [feat] plugin: optional API key for the AI summary LLM server
Servers that require authentication (e.g. vLLM or llama.cpp started with
--api-key, or an LLM server behind an authenticating reverse proxy) can
now be configured with an ai_summary.api_key, sent as "Authorization:
Bearer".

The key is administrator configuration only: there is no preference for
it, and it is only sent to the configured base_url.  Users can point the
ai_summary_server preference at a server of their own, and such a server
must not be handed the instance API key -- otherwise every user of the
instance could capture it.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-05 23:04:17 -07:00

133 lines
5.2 KiB
Python

# SPDX-License-Identifier: AGPL-3.0-or-later
"""Implementations needed for the AI summary plugin
(:py:obj:`searx.plugins.ai_summary`)."""
# pylint: disable=too-few-public-methods
# Struct fields aren't discovered in Python 3.14
# - https://github.com/searxng/searxng/issues/5284
from __future__ import annotations
__all__ = ["SettingsAISummary", "MODELS", "model_choices", "build_chat_messages"]
import msgspec
DEFAULT_SYSTEM_PROMPT = (
"You are a search assistant. Answer the user's search query concisely in"
" a few short paragraphs of plain text. If you are unsure or don't know"
" the answer, say so."
)
DEFAULT_SYSTEM_PROMPT_GROUNDED = (
"You are a search assistant. Answer the user's search query concisely in"
" a few short paragraphs of plain text, using the following search results"
" as context when they are relevant. If you are unsure or don't know the"
" answer, say so.\n\nSearch results:\n\n{context}"
)
MODELS: list[str] = []
"""List of model names a user can select from. Populated once at
application setup by :py:obj:`searx.plugins.ai_summary.SXNGPlugin.init`."""
class SettingsAISummary(msgspec.Struct, kw_only=True, forbid_unknown_fields=True):
"""Options for configuring the AI summary plugin.
.. code:: yaml
ai_summary:
base_url: "http://127.0.0.1:11434"
model: "llama3.2:3b"
models:
- "llama3.2:3b"
- "gemma3:4b"
"""
base_url: str = ""
"""Default base URL of the LLM server (e.g. ``http://127.0.0.1:11434``
for Ollama). Any server that implements the OpenAI chat completions API
works (Ollama, vLLM, llama.cpp, LM Studio, Hugging Face TGI, ...). Users
can set their own server URL in the preferences (``ai_summary_server``)
unless that preference is locked."""
api_key: str = ""
"""Optional API key of the LLM server in
:py:obj:`SettingsAISummary.base_url`, sent in an ``Authorization: Bearer``
header. Needed by servers that require authentication, e.g. vLLM or
llama.cpp started with ``--api-key``, or an LLM server behind an
authenticating reverse proxy.
There is intentionally no user preference for the API key, and the key is
**only** sent to :py:obj:`SettingsAISummary.base_url`: a user who points
the ``ai_summary_server`` preference at a server of their own gets no
``Authorization`` header, so the key can't be captured by a third party
(see :py:obj:`searx.plugins.ai_summary._server_api_key`)."""
model: str = ""
"""Name of the default model (e.g. ``llama3.2:3b``). If empty, the first
entry of :py:obj:`SettingsAISummary.models` is used. Users can set their
own model in the preferences (``ai_summary_model``) unless that preference
is locked."""
models: list[str] = []
"""List of model names suggested to the user in the preferences. If empty
and :py:obj:`SettingsAISummary.base_url` is set, the list is requested
once at application setup from the LLM server (``GET /v1/models``)."""
grounding: bool = False
"""Default of the ``ai_summary_grounding`` user preference: ground the
summary on the search results. Users can still opt in/out in the
preferences unless that preference is locked."""
connect_timeout: float = 5.0
"""Timeout (seconds) to establish a TCP connection to the LLM server."""
read_timeout: float = 30.0
"""Maximum gap (seconds) between two chunks of the token stream."""
stream_timeout: float = 120.0
"""Wall clock limit (seconds) for one completion."""
max_context_items: int = 5
"""Maximum number of search results accepted as grounding context."""
max_history_messages: int = 12
"""Maximum number of messages (follow-up chat history) per request."""
max_message_length: int = 4000
"""Maximum length (characters) of a single message or context snippet."""
system_prompt: str = DEFAULT_SYSTEM_PROMPT
"""System prompt used when the *grounding* preference is off."""
system_prompt_grounded: str = DEFAULT_SYSTEM_PROMPT_GROUNDED
"""System prompt used when the *grounding* preference is on. The
placeholder ``{context}`` is replaced by an enumeration of the search
results sent along with the query."""
def model_choices() -> list[str]:
"""Model names a user can select from in the preferences."""
return list(MODELS)
def build_chat_messages(
cfg: SettingsAISummary,
messages: list[dict[str, str]],
context: list[dict[str, str]] | None = None,
) -> list[dict[str, str]]:
"""Build the message list for the chat completions request from the
(already validated) request ``messages``, prepending a system prompt. When
``context`` items are given, the grounded system prompt is used and the
context items are serialized into its ``{context}`` placeholder."""
if context:
ctx_lines = [
f"[{no}] {item.get('title', '')}{item.get('snippet', '')} ({item.get('url', '')})"
for no, item in enumerate(context[: cfg.max_context_items], start=1)
]
system_prompt = cfg.system_prompt_grounded.replace("{context}", "\n".join(ctx_lines))
else:
system_prompt = cfg.system_prompt
return [{"role": "system", "content": system_prompt}, *messages]