Keep fixed tool parameters fixed when the model sends them

A parameter hidden from the model with a stored value is now always sent
with that value; a model that names the key anyway (by mistake, or because
a prompt told it to) no longer overrides it. 0 and false are real fixed
values; an empty value still means the parameter is left out.
This commit is contained in:
arc53-machine committed 2026-09-29 10:41:13 +01:00
1 parent bbf83f02b2
commit 34038ae1c2
3 files changed
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+20 -27
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@@ -14,6 +14,7 @@ from docsgpt.agents.default_tools import (
synthesized_default_tools,
)
from docsgpt import tracing
from docsgpt.agents.tool_pins import iter_parameters, llm_fills, resolve_arguments
from docsgpt.agents.tools.tool_action_parser import ToolActionParser
from docsgpt.agents.tools.tool_manager import ToolManager
from docsgpt.guardrails.types import Stage as GuardrailStage, resolve_tool_result
@@ -761,17 +762,22 @@ class ToolExecutor:
)
return result
def _build_tool_parameters(self, action: Dict) -> Dict:
def _build_tool_parameters(self, action: Dict, hidden: Optional[set] = None) -> Dict:
"""The JSON schema the model sees for ``action``.
Parameters the model does not fill (fixed values) and ``hidden`` ones
(values the connection fixes) are left out, so the model is never
asked for them.
"""
params = {"type": "object", "properties": {}, "required": []}
for param_type in ["query_params", "headers", "body", "parameters"]:
if param_type in action and action[param_type].get("properties"):
for k, v in action[param_type]["properties"].items():
if v.get("filled_by_llm", True):
params["properties"][k] = {
key: value for key, value in v.items() if key not in ("filled_by_llm", "value", "required")
}
if v.get("required", False):
params["required"].append(k)
for _section, k, v in iter_parameters(action):
if not llm_fills(v) or (hidden and k in hidden):
continue
params["properties"][k] = {
key: value for key, value in v.items() if key not in ("filled_by_llm", "value", "required")
}
if v.get("required", False):
params["required"].append(k)
return params
def _guardrail_tool_result(self, result: Any, tool_name: str, action_name: str) -> Any:
@@ -1393,23 +1399,10 @@ class ToolExecutor:
tool_call_data["access"] = action_access(tool_data.get("name"), action_data)
query_params, headers, body, parameters = {}, {}, {}, {}
param_types = {
"query_params": query_params,
"headers": headers,
"body": body,
"parameters": parameters,
}
for param_type, target_dict in param_types.items():
if param_type in action_data and action_data[param_type].get("properties"):
for param, details in action_data[param_type]["properties"].items():
if param not in call_args and "value" in details and details["value"]:
target_dict[param] = details["value"]
for param, value in call_args.items():
for param_type, target_dict in param_types.items():
if param_type in action_data and param in action_data[param_type].get("properties", {}):
target_dict[param] = value
# Fixed values win over whatever the model sent for the same key.
sections = resolve_arguments(action_data, call_args)
query_params, headers = sections["query_params"], sections["headers"]
body, parameters = sections["body"], sections["parameters"]
# Load tool (with caching)
from docsgpt.connectors.service import ConnectionUnavailable
+290
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@@ -0,0 +1,290 @@
"""Fixed ("pinned") tool parameters.
Every parameter of a stored tool action carries ``filled_by_llm`` and
``value``. A parameter with ``filled_by_llm`` false is hidden from the model;
when it also has a value, that value is *pinned*: it is sent on every call and
the model can neither see nor override it. An empty string means "no value":
the parameter is left out of the call (optional OpenAPI parameters are stored
that way), while ``0`` and ``false`` are real values.
The run-time rules live in :func:`resolve_arguments`; the helpers below
validate and apply pin changes coming from the API.
"""
from __future__ import annotations
import copy
from typing import Any, Iterable, Mapping, Optional
#: The places an action keeps parameter schemas: ``parameters`` for ordinary
#: tools and MCP, the other three for ``api_tool`` requests.
PARAM_SECTIONS = ("query_params", "headers", "body", "parameters")
_NUMERIC = {"integer": int, "number": float}
def _properties(action: Mapping, section: str) -> dict:
block = action.get(section)
if not isinstance(block, dict):
return {}
properties = block.get("properties")
return properties if isinstance(properties, dict) else {}
def iter_parameters(action: Mapping) -> Iterable[tuple[str, str, dict]]:
"""``(section, name, details)`` for every parameter schema of ``action``."""
for section in PARAM_SECTIONS:
for name, details in _properties(action, section).items():
if isinstance(details, dict):
yield section, name, details
def llm_fills(details: Mapping) -> bool:
"""Whether the model fills this parameter (the default when unset)."""
return bool(details.get("filled_by_llm", True))
def has_value(details: Mapping) -> bool:
"""Whether a parameter carries a value: anything but a missing, None or empty string."""
value = details.get("value")
return value is not None and value != ""
def is_pinned(details: Mapping) -> bool:
"""Whether the parameter is hidden from the model and always sent with its value."""
return not llm_fills(details) and has_value(details)
def pinned_names(action: Mapping) -> list[str]:
"""Names of the parameters of ``action`` that carry a pinned value."""
return [name for _section, name, details in iter_parameters(action) if is_pinned(details)]
def resolve_arguments(
action: Mapping,
llm_arguments: Mapping[str, Any],
connection_pins: Optional[Mapping[str, Any]] = None,
) -> dict[str, dict]:
"""The arguments a call runs with, per parameter section.
Only parameters the action declares are passed. For each one:
* a value the connection fixes (``connection_pins``, e.g. Telegram's
default chat) always wins;
* a parameter hidden from the model takes its stored value, or is left
out when it has none; whatever the model sent for it is ignored, so a
model that names the key anyway (a mistake, or a prompt injection)
changes nothing;
* any other parameter takes the model's value, falling back to its
stored default.
Args:
action: The stored action (``parameters`` / ``query_params`` /
``headers`` / ``body`` schemas with ``filled_by_llm`` and ``value``).
llm_arguments: The arguments the model sent.
connection_pins: Parameter name to a value the connection fixes.
Returns:
Section name to ``{parameter: value}`` for every section in
:data:`PARAM_SECTIONS` (empty dicts included).
"""
connection_pins = connection_pins or {}
resolved: dict[str, dict] = {section: {} for section in PARAM_SECTIONS}
for section, name, details in iter_parameters(action):
target = resolved[section]
if name in connection_pins:
target[name] = connection_pins[name]
elif not llm_fills(details):
if has_value(details):
target[name] = details["value"]
elif name in llm_arguments:
target[name] = llm_arguments[name]
elif has_value(details):
target[name] = details["value"]
return resolved
def coerce_value(details: Mapping, value: Any) -> Any:
"""Check a value for a pin against the parameter's declared type.
Strings typed into a form are converted for ``integer``, ``number`` and
``boolean`` parameters.
Raises:
ValueError: The value does not fit the type, or is empty.
"""
if value is None or value == "":
raise ValueError("A fixed value cannot be empty")
kind = details.get("type")
if isinstance(kind, list):
kind = next((k for k in kind if k != "null"), None)
if kind in _NUMERIC:
if isinstance(value, bool):
raise ValueError(f"Expected a {kind}")
try:
number = _NUMERIC[kind](value)
except (TypeError, ValueError):
raise ValueError(f"Expected a {kind}") from None
if kind == "integer" and isinstance(value, float) and not value.is_integer():
raise ValueError("Expected an integer")
return number
if kind == "boolean":
if isinstance(value, bool):
return value
if isinstance(value, str) and value.strip().lower() in ("true", "false"):
return value.strip().lower() == "true"
raise ValueError("Expected true or false")
if kind == "array":
if not isinstance(value, list):
raise ValueError("Expected a list")
return value
if kind == "object":
if not isinstance(value, dict):
raise ValueError("Expected an object")
return value
if kind in (None, "string"):
if not isinstance(value, (str, int, float, bool)):
raise ValueError("Expected text")
return str(value) if kind == "string" else value
return value
def set_pins(action: Mapping, pins: Mapping[str, Any]) -> dict:
"""Return ``action`` with ``pins`` applied.
Args:
action: A stored action.
pins: Parameter name to the value to always use, or None to let the
model decide again.
Raises:
ValueError: A parameter does not exist on the action, or a value does
not fit its type.
"""
updated = copy.deepcopy(dict(action))
known = {name: details for _section, name, details in iter_parameters(updated)}
for name, value in pins.items():
details = known.get(name)
if details is None:
raise ValueError(f"Unknown parameter: {name}")
if value is None:
details["filled_by_llm"] = True
details["value"] = ""
else:
details["value"] = coerce_value(details, value)
details["filled_by_llm"] = False
return updated
class PinChangeRefused(PermissionError):
"""Someone other than the tool's owner tried to change a fixed value."""
_ACTION_KEYS = ("active", "require_approval", "description")
_PARAM_KEYS = ("filled_by_llm", "value", "description")
def _pin_state(details: Mapping) -> tuple:
return (llm_fills(details), details.get("value") if has_value(details) else None)
def merge_submitted_actions(stored: list, submitted: Any, *, may_change_pins: bool) -> list:
"""Validate a full list of actions sent by a client against the stored ones.
The stored actions are the schema: a client can switch actions on and off,
change approval and descriptions and (the owner only) fixed values, but
cannot add actions or parameters, or change a parameter's type.
Args:
stored: The tool's stored actions.
submitted: What the client sent (untrusted).
may_change_pins: False for a team editor: any change to
``filled_by_llm`` or ``value`` is refused.
Returns:
The actions to store: every stored action, updated from the
submission.
Raises:
ValueError: The submission is malformed or names an unknown action or
parameter, or a fixed value does not fit its parameter.
PinChangeRefused: ``may_change_pins`` is False and a fixed value changed.
"""
if not isinstance(submitted, list):
raise ValueError("actions must be a list")
by_name = {a.get("name"): a for a in stored if isinstance(a, dict) and a.get("name")}
seen: set = set()
updates: dict[str, dict] = {}
for entry in submitted:
if not isinstance(entry, dict) or not isinstance(entry.get("name"), str):
raise ValueError("Each action needs a name")
name = entry["name"]
if name not in by_name:
raise ValueError(f"Unknown action: {name}")
if name in seen:
raise ValueError(f"Duplicate action: {name}")
seen.add(name)
updates[name] = entry
merged = []
for action in stored:
if not isinstance(action, dict) or action.get("name") not in updates:
merged.append(action)
continue
entry = updates[action["name"]]
result = copy.deepcopy(action)
for key in _ACTION_KEYS:
if key in entry:
value = entry[key]
if key == "description" and not isinstance(value, str):
raise ValueError("description must be text")
result[key] = bool(value) if key != "description" else value
for section in PARAM_SECTIONS:
sent = _properties(entry, section)
if not sent:
continue
properties = _properties(result, section)
for param, sent_details in sent.items():
details = properties.get(param)
if details is None or not isinstance(details, dict):
raise ValueError(f"Unknown parameter {param} on {action['name']}")
if not isinstance(sent_details, dict):
raise ValueError(f"Parameter {param} must be an object")
before = _pin_state(details)
for key in _PARAM_KEYS:
if key in sent_details:
details[key] = sent_details[key]
details["filled_by_llm"] = llm_fills(details)
if _pin_state(details) == before:
continue
if not may_change_pins:
raise PinChangeRefused("Only the tool's owner can change fixed values")
if is_pinned(details):
details["value"] = coerce_value(details, details["value"])
merged.append(result)
return merged
def carry_pins_between(previous: Optional[list], fresh: list) -> list:
""":func:`carry_pins` for whole action lists, matching actions by name."""
old = {a.get("name"): a for a in previous or [] if isinstance(a, dict)}
return [carry_pins(old.get(a.get("name")), a) if isinstance(a, dict) else a for a in fresh]
def carry_pins(previous: Optional[Mapping], fresh: Mapping) -> dict:
"""Copy fixed values from an action's old copy onto its re-discovered one.
Parameters that still exist keep ``filled_by_llm`` and ``value``; removed
ones are gone with the new schema.
"""
result = copy.deepcopy(dict(fresh))
if not previous:
return result
old = {(section, name): details for section, name, details in iter_parameters(previous)}
for section, name, details in iter_parameters(result):
before = old.get((section, name))
if before is None:
continue
details["filled_by_llm"] = llm_fills(before)
details["value"] = before.get("value", "")
return result
+240
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@@ -0,0 +1,240 @@
"""Fixed ("pinned") tool parameters: the model never sees or overrides them."""
from unittest.mock import Mock
import pytest
from docsgpt.agents.tool_executor import ToolExecutor
def _action(**properties):
return {
"name": "telegram_send_message",
"description": "Send a message",
"active": True,
"parameters": {"type": "object", "properties": properties},
}
def _llm(description="", **extra):
return {"type": "string", "description": description, "filled_by_llm": True, "value": "", **extra}
def _pinned(value, type_="string"):
return {"type": type_, "description": "", "filled_by_llm": False, "value": value}
def _run(executor, tools_dict, call_args, monkeypatch):
monkeypatch.setattr(
"docsgpt.agents.tool_executor.ToolActionParser",
lambda _cls, **kw: Mock(parse_args=Mock(return_value=("t1", "telegram_send_message", call_args))),
)
call = Mock()
call.name = "telegram_send_message"
call.id = "c1"
call.arguments = "{}"
gen = executor.execute(tools_dict, call, "MockLLM")
while True:
try:
next(gen)
except StopIteration as stop:
return stop.value
def _tools(action):
return {
"t1": {
"id": "00000000-0000-0000-0000-000000000001",
"name": "telegram",
"config": {},
"actions": [action],
}
}
@pytest.mark.unit
class TestPinnedValuesAtRunTime:
def test_llm_cannot_override_a_pinned_value(self, mock_tool_manager, monkeypatch):
"""A model that sends the pinned key anyway (a mistake, or a prompt
injection naming another chat) still sends to the pinned chat."""
tool = mock_tool_manager.load_tool.return_value
action = _action(text=_llm(), chat_id=_pinned("111"))
_run(ToolExecutor(user="u"), _tools(action), {"text": "hi", "chat_id": "666"}, monkeypatch)
tool.execute_action.assert_called_once_with("telegram_send_message", text="hi", chat_id="111")
@pytest.mark.parametrize("value", [0, False])
def test_falsy_pins_are_honoured(self, mock_tool_manager, monkeypatch, value):
tool = mock_tool_manager.load_tool.return_value
action = _action(text=_llm(), limit=_pinned(value, "integer"))
_run(ToolExecutor(user="u"), _tools(action), {"text": "hi", "limit": 50}, monkeypatch)
tool.execute_action.assert_called_once_with("telegram_send_message", text="hi", limit=value)
def test_hidden_parameter_without_a_value_is_omitted_even_if_the_llm_sends_it(
self, mock_tool_manager, monkeypatch,
):
"""An empty fixed value means "leave it out" (an OpenAPI optional
parameter); the model was never shown it, so its value is dropped."""
tool = mock_tool_manager.load_tool.return_value
action = _action(text=_llm(), chat_id=_pinned(""))
_run(ToolExecutor(user="u"), _tools(action), {"text": "hi", "chat_id": "666"}, monkeypatch)
tool.execute_action.assert_called_once_with("telegram_send_message", text="hi")
def test_llm_filled_parameter_keeps_its_default_when_omitted(self, mock_tool_manager, monkeypatch):
tool = mock_tool_manager.load_tool.return_value
action = _action(text=_llm(), chat_id=_llm(value="42"))
_run(ToolExecutor(user="u"), _tools(action), {"text": "hi"}, monkeypatch)
tool.execute_action.assert_called_once_with("telegram_send_message", text="hi", chat_id="42")
def test_llm_filled_parameter_takes_the_llm_value(self, mock_tool_manager, monkeypatch):
tool = mock_tool_manager.load_tool.return_value
action = _action(text=_llm(), chat_id=_llm(value="42"))
_run(ToolExecutor(user="u"), _tools(action), {"text": "hi", "chat_id": "7"}, monkeypatch)
tool.execute_action.assert_called_once_with("telegram_send_message", text="hi", chat_id="7")
def test_unknown_llm_arguments_are_dropped(self, mock_tool_manager, monkeypatch):
tool = mock_tool_manager.load_tool.return_value
action = _action(text=_llm())
_run(ToolExecutor(user="u"), _tools(action), {"text": "hi", "token": "x"}, monkeypatch)
tool.execute_action.assert_called_once_with("telegram_send_message", text="hi")
def test_api_tool_pinned_header_is_not_overridden(self, mock_tool_manager, monkeypatch):
executor = ToolExecutor(user="u")
monkeypatch.setattr(
"docsgpt.agents.tool_executor.ToolActionParser",
lambda _cls, **kw: Mock(parse_args=Mock(return_value=("t1", "get_item", {"id": "1", "X-Tenant": "b"}))),
)
tools_dict = {
"t1": {
"id": "00000000-0000-0000-0000-000000000001",
"name": "api_tool",
"config": {
"actions": {
"get_item": {
"name": "get_item",
"url": "https://api.example.com/items",
"method": "GET",
"active": True,
"headers": {"properties": {"X-Tenant": _pinned("a")}},
"query_params": {"properties": {"id": _llm()}},
"body": {"properties": {}},
}
}
},
}
}
call = Mock()
call.name = "get_item"
call.id = "c1"
gen = executor.execute(tools_dict, call, "MockLLM")
while True:
try:
next(gen)
except StopIteration:
break
_, kwargs = mock_tool_manager.load_tool.call_args
assert kwargs["tool_config"]["headers"] == {"X-Tenant": "a"}
assert kwargs["tool_config"]["query_params"] == {"id": "1"}
@pytest.mark.unit
class TestPinnedValuesInTheSchema:
def test_pinned_parameter_is_not_shown_to_the_llm(self):
executor = ToolExecutor(user="u")
action = _action(text=_llm(), chat_id=_pinned("111"), limit=_pinned(0, "integer"))
functions = executor.prepare_tools_for_llm(_tools(action))
params = functions[0]["function"]["parameters"]
assert set(params["properties"]) == {"text"}
def test_pinned_parameter_is_dropped_from_the_required_list(self):
executor = ToolExecutor(user="u")
action = _action(text=_llm(required=True), chat_id={**_pinned("111"), "required": True})
params = executor.prepare_tools_for_llm(_tools(action))[0]["function"]["parameters"]
assert params["required"] == ["text"]
@pytest.mark.unit
class TestPinHelpers:
def test_set_pins_fixes_and_releases_parameters(self):
from docsgpt.agents.tool_pins import set_pins
action = _action(text=_llm(), chat_id=_llm())
pinned = set_pins(action, {"chat_id": "123"})
assert pinned["parameters"]["properties"]["chat_id"] == {
"type": "string", "description": "", "filled_by_llm": False, "value": "123",
}
released = set_pins(pinned, {"chat_id": None})
assert released["parameters"]["properties"]["chat_id"]["filled_by_llm"] is True
assert released["parameters"]["properties"]["chat_id"]["value"] == ""
# The input is not modified.
assert action["parameters"]["properties"]["chat_id"]["filled_by_llm"] is True
def test_set_pins_rejects_unknown_parameters(self):
from docsgpt.agents.tool_pins import set_pins
with pytest.raises(ValueError):
set_pins(_action(text=_llm()), {"token": "x"})
@pytest.mark.parametrize(
"type_, value, expected",
[
("integer", "5", 5),
("integer", 0, 0),
("number", "2.5", 2.5),
("boolean", "false", False),
("boolean", True, True),
("string", 12, "12"),
],
)
def test_coerce_value(self, type_, value, expected):
from docsgpt.agents.tool_pins import coerce_value
assert coerce_value({"type": type_}, value) == expected
@pytest.mark.parametrize(
"type_, value",
[("integer", "five"), ("integer", 2.5), ("boolean", "maybe"), ("string", ""), ("string", None),
("string", {"a": 1}), ("array", "x")],
)
def test_coerce_value_rejects(self, type_, value):
from docsgpt.agents.tool_pins import coerce_value
with pytest.raises(ValueError):
coerce_value({"type": type_}, value)
def test_merge_keeps_schema_and_ignores_type_changes(self):
from docsgpt.agents.tool_pins import merge_submitted_actions
stored = [_action(text=_llm(), chat_id=_llm())]
merged = merge_submitted_actions(stored, [{
"name": "telegram_send_message",
"parameters": {"properties": {"chat_id": {"type": "object", "filled_by_llm": False, "value": "9"}}},
}], may_change_pins=True)
chat_id = merged[0]["parameters"]["properties"]["chat_id"]
assert chat_id["type"] == "string"
assert chat_id["value"] == "9" and chat_id["filled_by_llm"] is False
def test_merge_refuses_pin_changes_without_permission(self):
from docsgpt.agents.tool_pins import PinChangeRefused, merge_submitted_actions
stored = [_action(text=_llm(), chat_id=_pinned("111"))]
with pytest.raises(PinChangeRefused):
merge_submitted_actions(stored, [{
"name": "telegram_send_message",
"parameters": {"properties": {"chat_id": {"filled_by_llm": True}}},
}], may_change_pins=False)
# Resending the stored values unchanged is fine.
merged = merge_submitted_actions(stored, [{
"name": "telegram_send_message",
"active": False,
"parameters": {"properties": {"chat_id": {"filled_by_llm": False, "value": "111"}}},
}], may_change_pins=False)
assert merged[0]["active"] is False
def test_carry_pins(self):
from docsgpt.agents.tool_pins import carry_pins
old = _action(q=_llm(), team=_pinned("ENG"))
fresh = _action(q={"type": "string", "filled_by_llm": True, "value": ""}, team={"type": "string"})
carried = carry_pins(old, fresh)
assert carried["parameters"]["properties"]["team"]["value"] == "ENG"
assert carried["parameters"]["properties"]["team"]["filled_by_llm"] is False