refactor(agents): delete dead single-agent-only middleware

file_intent (FileIntentMiddleware) and flatten_system
(FlattenSystemMessageMiddleware) were only ever instantiated in the
single-agent chat_deepagent stack, which was removed in 14bbea085. They
have no production consumer in multi_agent_chat. Delete both modules and
their unit tests.

Also drop the vestigial KnowledgeBaseSearchMiddleware alias (= the live
KnowledgePriorityMiddleware); its tests now target the real class so the
behavior coverage is preserved. Trim the three barrel/__all__ entries and
strip the now-dead class names from comments.
This commit is contained in:
CREDO23 2026-06-05 11:15:13 +02:00
parent 21509e7eca
commit afa51e97cf
10 changed files with 19 additions and 1161 deletions

View file

@ -50,8 +50,8 @@ class SurfSenseContextSchema:
(cloud filesystem mode). Surfaced as ``[USER-MENTIONED]`` (cloud filesystem mode). Surfaced as ``[USER-MENTIONED]``
entries in ``<priority_documents>`` so the agent prioritises entries in ``<priority_documents>`` so the agent prioritises
walking those folders with ``ls`` / ``find_documents``. walking those folders with ``ls`` / ``find_documents``.
file_operation_contract: One-shot file operation contract emitted file_operation_contract: One-shot file operation contract for the
by ``FileIntentMiddleware`` for the upcoming turn. upcoming turn (reserved; not currently populated).
turn_id / request_id: Correlation IDs surfaced by the streaming turn_id / request_id: Correlation IDs surfaced by the streaming
task; populated for telemetry. task; populated for telemetry.

View file

@ -21,18 +21,11 @@ from app.agents.shared.middleware.dedup_tool_calls import (
DedupHITLToolCallsMiddleware, DedupHITLToolCallsMiddleware,
) )
from app.agents.shared.middleware.doom_loop import DoomLoopMiddleware from app.agents.shared.middleware.doom_loop import DoomLoopMiddleware
from app.agents.shared.middleware.file_intent import (
FileIntentMiddleware,
)
from app.agents.shared.middleware.flatten_system import (
FlattenSystemMessageMiddleware,
)
from app.agents.shared.middleware.kb_persistence import ( from app.agents.shared.middleware.kb_persistence import (
KnowledgeBasePersistenceMiddleware, KnowledgeBasePersistenceMiddleware,
commit_staged_filesystem_state, commit_staged_filesystem_state,
) )
from app.agents.shared.middleware.knowledge_search import ( from app.agents.shared.middleware.knowledge_search import (
KnowledgeBaseSearchMiddleware,
KnowledgePriorityMiddleware, KnowledgePriorityMiddleware,
) )
from app.agents.shared.middleware.knowledge_tree import ( from app.agents.shared.middleware.knowledge_tree import (
@ -56,10 +49,7 @@ __all__ = [
"ClearToolUsesEdit", "ClearToolUsesEdit",
"DedupHITLToolCallsMiddleware", "DedupHITLToolCallsMiddleware",
"DoomLoopMiddleware", "DoomLoopMiddleware",
"FileIntentMiddleware",
"FlattenSystemMessageMiddleware",
"KnowledgeBasePersistenceMiddleware", "KnowledgeBasePersistenceMiddleware",
"KnowledgeBaseSearchMiddleware",
"KnowledgePriorityMiddleware", "KnowledgePriorityMiddleware",
"KnowledgeTreeMiddleware", "KnowledgeTreeMiddleware",
"MemoryInjectionMiddleware", "MemoryInjectionMiddleware",

View file

@ -94,7 +94,7 @@ Respond ONLY with the structured summary. Do not include any text before or afte
PROTECTED_SYSTEM_PREFIXES: tuple[str, ...] = ( PROTECTED_SYSTEM_PREFIXES: tuple[str, ...] = (
"<priority_documents>", # KnowledgePriorityMiddleware "<priority_documents>", # KnowledgePriorityMiddleware
"<workspace_tree>", # KnowledgeTreeMiddleware "<workspace_tree>", # KnowledgeTreeMiddleware
"<file_operation_contract>", # FileIntentMiddleware "<file_operation_contract>", # reserved file-operation contract prefix
"<user_memory>", # MemoryInjectionMiddleware "<user_memory>", # MemoryInjectionMiddleware
"<team_memory>", # MemoryInjectionMiddleware "<team_memory>", # MemoryInjectionMiddleware
"<user_name>", # MemoryInjectionMiddleware "<user_name>", # MemoryInjectionMiddleware

View file

@ -1,334 +0,0 @@
"""Semantic file-intent routing middleware for new chat turns.
This middleware classifies the latest human turn into a small intent set:
- chat_only
- file_write
- file_read
For ``file_write`` turns it injects a strict system contract so the model
uses filesystem tools before claiming success, and provides a deterministic
fallback path when no filename is specified by the user.
"""
from __future__ import annotations
import json
import logging
import re
from datetime import UTC, datetime
from enum import StrEnum
from typing import Any
from langchain.agents.middleware import AgentMiddleware, AgentState
from langchain_core.language_models import BaseChatModel
from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
from langgraph.runtime import Runtime
from pydantic import BaseModel, Field, ValidationError
logger = logging.getLogger(__name__)
class FileOperationIntent(StrEnum):
CHAT_ONLY = "chat_only"
FILE_WRITE = "file_write"
FILE_READ = "file_read"
class FileIntentPlan(BaseModel):
intent: FileOperationIntent = Field(
description="Primary user intent for this turn."
)
confidence: float = Field(
ge=0.0,
le=1.0,
default=0.5,
description="Model confidence in the selected intent.",
)
suggested_filename: str | None = Field(
default=None,
description="Optional filename (e.g. notes.md) inferred from user request.",
)
suggested_directory: str | None = Field(
default=None,
description=(
"Optional directory path (e.g. /reports/q2 or reports/q2) inferred from "
"user request."
),
)
suggested_path: str | None = Field(
default=None,
description=(
"Optional full file path (e.g. /reports/q2/summary.md). If present, this "
"takes precedence over suggested_directory + suggested_filename."
),
)
def _extract_text_from_message(message: BaseMessage) -> str:
content = getattr(message, "content", "")
if isinstance(content, str):
return content
if isinstance(content, list):
parts: list[str] = []
for item in content:
if isinstance(item, str):
parts.append(item)
elif isinstance(item, dict) and item.get("type") == "text":
parts.append(str(item.get("text", "")))
return "\n".join(part for part in parts if part)
return str(content)
def _extract_json_payload(text: str) -> str:
stripped = text.strip()
fenced = re.search(r"```(?:json)?\s*(\{.*?\})\s*```", stripped, re.DOTALL)
if fenced:
return fenced.group(1)
start = stripped.find("{")
end = stripped.rfind("}")
if start != -1 and end != -1 and end > start:
return stripped[start : end + 1]
return stripped
def _sanitize_filename(value: str) -> str:
name = re.sub(r"[\\/:*?\"<>|]+", "_", value).strip()
name = re.sub(r"\s+", "-", name)
name = name.strip("._-")
if not name:
name = "note"
if len(name) > 80:
name = name[:80].rstrip("-_.")
return name
def _sanitize_path_segment(value: str) -> str:
segment = re.sub(r"[\\/:*?\"<>|]+", "_", value).strip()
segment = re.sub(r"\s+", "_", segment)
segment = segment.strip("._-")
return segment
def _normalize_directory(value: str) -> str:
raw = value.strip().replace("\\", "/")
raw = raw.strip("/")
if not raw:
return ""
parts = [_sanitize_path_segment(part) for part in raw.split("/") if part.strip()]
parts = [part for part in parts if part]
return "/".join(parts)
def _normalize_file_path(value: str) -> str:
raw = value.strip().replace("\\", "/").strip()
if not raw:
return ""
had_trailing_slash = raw.endswith("/")
raw = raw.strip("/")
if not raw:
return ""
parts = [_sanitize_path_segment(part) for part in raw.split("/") if part.strip()]
parts = [part for part in parts if part]
if not parts:
return ""
if had_trailing_slash:
return f"/{'/'.join(parts)}/"
return f"/{'/'.join(parts)}"
def _infer_directory_from_user_text(user_text: str) -> str | None:
patterns = (
r"\b(?:in|inside|under)\s+(?:the\s+)?([a-zA-Z0-9 _\-/]+?)\s+folder\b",
r"\b(?:in|inside|under)\s+([a-zA-Z0-9 _\-/]+?)\b",
)
lowered = user_text.lower()
for pattern in patterns:
match = re.search(pattern, lowered, flags=re.IGNORECASE)
if not match:
continue
candidate = match.group(1).strip()
if candidate in {"the", "a", "an"}:
continue
normalized = _normalize_directory(candidate)
if normalized:
return normalized
return None
def _fallback_path(
suggested_filename: str | None,
*,
suggested_directory: str | None = None,
suggested_path: str | None = None,
user_text: str,
) -> str:
inferred_dir = _infer_directory_from_user_text(user_text)
sanitized_filename = ""
if suggested_filename:
sanitized_filename = _sanitize_filename(suggested_filename)
if sanitized_filename.lower().endswith(".txt"):
sanitized_filename = f"{sanitized_filename[:-4]}.md"
if not sanitized_filename:
sanitized_filename = "notes.md"
elif "." not in sanitized_filename:
sanitized_filename = f"{sanitized_filename}.md"
normalized_suggested_path = (
_normalize_file_path(suggested_path) if suggested_path else ""
)
if normalized_suggested_path:
if normalized_suggested_path.endswith("/"):
return f"{normalized_suggested_path.rstrip('/')}/{sanitized_filename}"
return normalized_suggested_path
directory = _normalize_directory(suggested_directory or "")
if not directory and inferred_dir:
directory = inferred_dir
if directory:
return f"/{directory}/{sanitized_filename}"
return f"/{sanitized_filename}"
def _build_classifier_prompt(*, recent_conversation: str, user_text: str) -> str:
return (
"Classify the latest user request into a filesystem intent for an AI agent.\n"
"Return JSON only with this exact schema:\n"
'{"intent":"chat_only|file_write|file_read","confidence":0.0,"suggested_filename":"string or null","suggested_directory":"string or null","suggested_path":"string or null"}\n\n'
"Rules:\n"
"- Use semantic intent, not literal keywords.\n"
"- file_write: user asks to create/save/write/update/edit content as a file.\n"
"- file_read: user asks to open/read/list/search existing files.\n"
"- chat_only: conversational/analysis responses without required file operations.\n"
"- For file_write, choose a concise semantic suggested_filename and match the requested format.\n"
"- If the user mentions a folder/directory, populate suggested_directory.\n"
"- If user specifies an explicit full path, populate suggested_path.\n"
"- Use extensions that match user intent (e.g. .md, .json, .yaml, .csv, .py, .ts, .js, .html, .css, .sql).\n"
"- Do not use .txt; prefer .md for generic text notes.\n"
"- Do not include dates or timestamps in suggested_filename unless explicitly requested.\n"
"- Never include markdown or explanation.\n\n"
f"Recent conversation:\n{recent_conversation or '(none)'}\n\n"
f"Latest user message:\n{user_text}"
)
def _build_recent_conversation(
messages: list[BaseMessage], *, max_messages: int = 6
) -> str:
rows: list[str] = []
filtered: list[tuple[str, BaseMessage]] = []
for msg in messages:
role: str | None = None
if isinstance(msg, HumanMessage):
role = "user"
elif isinstance(msg, AIMessage):
if getattr(msg, "tool_calls", None):
continue
role = "assistant"
else:
continue
filtered.append((role, msg))
for role, msg in filtered[-max_messages:]:
text = re.sub(r"\s+", " ", _extract_text_from_message(msg)).strip()
if text:
rows.append(f"{role}: {text[:280]}")
return "\n".join(rows)
class FileIntentMiddleware(AgentMiddleware): # type: ignore[type-arg]
"""Classify file intent and inject a strict file-write contract."""
tools = ()
def __init__(self, *, llm: BaseChatModel | None = None) -> None:
self.llm = llm
async def _classify_intent(
self, *, messages: list[BaseMessage], user_text: str
) -> FileIntentPlan:
if self.llm is None:
return FileIntentPlan(intent=FileOperationIntent.CHAT_ONLY, confidence=0.0)
prompt = _build_classifier_prompt(
recent_conversation=_build_recent_conversation(messages),
user_text=user_text,
)
try:
response = await self.llm.ainvoke(
[HumanMessage(content=prompt)],
config={"tags": ["surfsense:internal"]},
)
payload = json.loads(
_extract_json_payload(_extract_text_from_message(response))
)
plan = FileIntentPlan.model_validate(payload)
return plan
except (json.JSONDecodeError, ValidationError, ValueError) as exc:
logger.warning("File intent classifier returned invalid output: %s", exc)
except Exception as exc: # pragma: no cover - defensive fallback
logger.warning("File intent classifier failed: %s", exc)
return FileIntentPlan(intent=FileOperationIntent.CHAT_ONLY, confidence=0.0)
async def abefore_agent( # type: ignore[override]
self,
state: AgentState,
runtime: Runtime[Any],
) -> dict[str, Any] | None:
del runtime
messages = state.get("messages") or []
if not messages:
return None
last_human: HumanMessage | None = None
for msg in reversed(messages):
if isinstance(msg, HumanMessage):
last_human = msg
break
if last_human is None:
return None
user_text = _extract_text_from_message(last_human).strip()
if not user_text:
return None
plan = await self._classify_intent(messages=messages, user_text=user_text)
suggested_path = _fallback_path(
plan.suggested_filename,
suggested_directory=plan.suggested_directory,
suggested_path=plan.suggested_path,
user_text=user_text,
)
contract = {
"intent": plan.intent.value,
"confidence": plan.confidence,
"suggested_path": suggested_path,
"timestamp": datetime.now(UTC).isoformat(),
"turn_id": state.get("turn_id", ""),
}
if plan.intent != FileOperationIntent.FILE_WRITE:
return {"file_operation_contract": contract}
contract_msg = SystemMessage(
content=(
"<file_operation_contract>\n"
"This turn intent is file_write.\n"
f"Suggested default path: {suggested_path}\n"
"Rules:\n"
"- You MUST call write_file or edit_file before claiming success.\n"
"- If no path is provided by the user, use the suggested default path.\n"
"- Do not claim a file was created/updated unless tool output confirms it.\n"
"- If the write/edit fails, clearly report failure instead of success.\n"
"- Do not include timestamps or dates in generated file content unless the user explicitly asks for them.\n"
"- For open-ended requests (e.g., random note), generate useful concrete content, not placeholders.\n"
"</file_operation_contract>"
)
)
# Insert just before the latest human turn so it applies to this request.
new_messages = list(messages)
insert_at = max(len(new_messages) - 1, 0)
new_messages.insert(insert_at, contract_msg)
return {"messages": new_messages, "file_operation_contract": contract}

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@ -1,233 +0,0 @@
r"""Coalesce multi-block system messages into a single text block.
Several middlewares in our deepagent stack each call
``append_to_system_message`` on the way down to the model
(``TodoListMiddleware``, ``SurfSenseFilesystemMiddleware``,
``SkillsMiddleware``, ``SubAgentMiddleware`` ). By the time the
request reaches the LLM, the system message has 5+ separate text blocks.
Anthropic enforces a hard cap of **4 ``cache_control`` blocks per
request**, and we configure 2 injection points
(``index: 0`` + ``index: -1``). With ``index: 0`` always targeting
the prepended ``request.system_message``, this middleware is the
defensive partner: it guarantees that "the system block" is *one*
content block, so LiteLLM's ``AnthropicCacheControlHook`` and any
OpenRouterAnthropic transformer can never multiply our budget into
several breakpoints by spreading ``cache_control`` across multiple
text blocks of a multi-block system content.
Without flattening we used to see::
OpenrouterException - {"error":{"message":"Provider returned error",
"code":400,"metadata":{"raw":"...A maximum of 4 blocks with
cache_control may be provided. Found 5."}}}
(Same error class documented in
https://github.com/BerriAI/litellm/issues/15696 and
https://github.com/BerriAI/litellm/issues/20485 the litellm-side fix
in PR #15395 covers the litellm transformer but does not protect us
when the OpenRouter SaaS itself does the redistribution.)
A separate fix in :mod:`app.agents.shared.prompt_caching` (switching
the first injection point from ``role: system`` to ``index: 0``)
neutralises the *primary* cause of the same 400 multiple
``SystemMessage``\ s injected by ``before_agent`` middlewares
(priority/tree/memory/file-intent/anonymous-doc) accumulating across
turns, each tagged with ``cache_control`` by the ``role: system``
matcher. This middleware remains useful as defence-in-depth against
the multi-block redistribution path.
Placement: innermost on the system-message-mutation chain, after every
appender (``todo``/``filesystem``/``skills``/``subagents``) and after
summarization, but before ``noop``/``retry``/``fallback`` so each retry
attempt sees a flattened payload.
Idempotent: a string-content system message is left untouched. A list
that contains anything other than plain text blocks (e.g. an image) is
also left untouched those are rare on system messages and we'd lose
the non-text payload by joining.
"""
from __future__ import annotations
import logging
from collections.abc import Awaitable, Callable
from typing import Any
from langchain.agents.middleware.types import (
AgentMiddleware,
AgentState,
ContextT,
ModelRequest,
ModelResponse,
ResponseT,
)
from langchain_core.messages import SystemMessage
logger = logging.getLogger(__name__)
def _flatten_text_blocks(content: list[Any]) -> str | None:
"""Return joined text if every block is a plain ``{"type": "text"}``.
Returns ``None`` when the list contains anything that isn't a text
block we can safely concatenate (image, audio, file, non-standard
blocks, dicts with extra non-cache_control fields). The caller
leaves the original content untouched in that case rather than
silently dropping payload.
``cache_control`` on individual blocks is intentionally discarded
the whole point of flattening is to let LiteLLM's
``cache_control_injection_points`` re-place a single breakpoint on
the resulting one-block system content.
"""
chunks: list[str] = []
for block in content:
if isinstance(block, str):
chunks.append(block)
continue
if not isinstance(block, dict):
return None
if block.get("type") != "text":
return None
text = block.get("text")
if not isinstance(text, str):
return None
chunks.append(text)
return "\n\n".join(chunks)
def _flattened_request(
request: ModelRequest[ContextT],
) -> ModelRequest[ContextT] | None:
"""Return a request with system_message flattened, or ``None`` for no-op."""
sys_msg = request.system_message
if sys_msg is None:
return None
content = sys_msg.content
if not isinstance(content, list) or len(content) <= 1:
return None
flattened = _flatten_text_blocks(content)
if flattened is None:
return None
new_sys = SystemMessage(
content=flattened,
additional_kwargs=dict(sys_msg.additional_kwargs),
response_metadata=dict(sys_msg.response_metadata),
)
if sys_msg.id is not None:
new_sys.id = sys_msg.id
return request.override(system_message=new_sys)
def _diagnostic_summary(request: ModelRequest[Any]) -> str:
"""One-line dump of cache_control-relevant request shape.
Temporary diagnostic to prove where the ``Found N`` cache_control
breakpoints are coming from when Anthropic 400s. Removed once the
root cause is confirmed and a fix is in place.
"""
sys_msg = request.system_message
if sys_msg is None:
sys_shape = "none"
elif isinstance(sys_msg.content, str):
sys_shape = f"str(len={len(sys_msg.content)})"
elif isinstance(sys_msg.content, list):
sys_shape = f"list(blocks={len(sys_msg.content)})"
else:
sys_shape = f"other({type(sys_msg.content).__name__})"
role_hist: list[str] = []
multi_block_msgs = 0
msgs_with_cc = 0
sys_msgs_in_history = 0
for m in request.messages:
mtype = getattr(m, "type", type(m).__name__)
role_hist.append(mtype)
if isinstance(m, SystemMessage):
sys_msgs_in_history += 1
c = getattr(m, "content", None)
if isinstance(c, list):
multi_block_msgs += 1
for blk in c:
if isinstance(blk, dict) and "cache_control" in blk:
msgs_with_cc += 1
break
if "cache_control" in getattr(m, "additional_kwargs", {}) or {}:
msgs_with_cc += 1
tools = request.tools or []
tools_with_cc = 0
for t in tools:
if isinstance(t, dict) and (
"cache_control" in t or "cache_control" in t.get("function", {})
):
tools_with_cc += 1
return (
f"sys={sys_shape} msgs={len(request.messages)} "
f"sys_msgs_in_history={sys_msgs_in_history} "
f"multi_block_msgs={multi_block_msgs} pre_existing_msg_cc={msgs_with_cc} "
f"tools={len(tools)} pre_existing_tool_cc={tools_with_cc} "
f"roles={role_hist[-8:]}"
)
class FlattenSystemMessageMiddleware(
AgentMiddleware[AgentState[ResponseT], ContextT, ResponseT]
):
"""Collapse a multi-text-block system message to a single string.
Sits innermost on the system-message-mutation chain so it observes
every middleware's contribution. Has no other side effect — the
body of every block is preserved, just joined with ``"\\n\\n"``.
"""
def __init__(self) -> None:
super().__init__()
self.tools = []
def wrap_model_call( # type: ignore[override]
self,
request: ModelRequest[ContextT],
handler: Callable[[ModelRequest[ContextT]], ModelResponse[ResponseT]],
) -> Any:
if logger.isEnabledFor(logging.DEBUG):
logger.debug("[flatten_system_diag] %s", _diagnostic_summary(request))
flattened = _flattened_request(request)
if flattened is not None:
if logger.isEnabledFor(logging.DEBUG):
logger.debug(
"[flatten_system] collapsed %d system blocks to one",
len(request.system_message.content), # type: ignore[arg-type, union-attr]
)
return handler(flattened)
return handler(request)
async def awrap_model_call( # type: ignore[override]
self,
request: ModelRequest[ContextT],
handler: Callable[
[ModelRequest[ContextT]], Awaitable[ModelResponse[ResponseT]]
],
) -> Any:
if logger.isEnabledFor(logging.DEBUG):
logger.debug("[flatten_system_diag] %s", _diagnostic_summary(request))
flattened = _flattened_request(request)
if flattened is not None:
if logger.isEnabledFor(logging.DEBUG):
logger.debug(
"[flatten_system] collapsed %d system blocks to one",
len(request.system_message.content), # type: ignore[arg-type, union-attr]
)
return await handler(flattened)
return await handler(request)
__all__ = [
"FlattenSystemMessageMiddleware",
"_flatten_text_blocks",
"_flattened_request",
]

View file

@ -1049,12 +1049,7 @@ class KnowledgePriorityMiddleware(AgentMiddleware): # type: ignore[type-arg]
return priority, matched_chunk_ids return priority, matched_chunk_ids
# Backwards-compatible alias for any external imports.
KnowledgeBaseSearchMiddleware = KnowledgePriorityMiddleware
__all__ = [ __all__ = [
"KnowledgeBaseSearchMiddleware",
"KnowledgePriorityMiddleware", "KnowledgePriorityMiddleware",
"browse_recent_documents", "browse_recent_documents",
"fetch_mentioned_documents", "fetch_mentioned_documents",

View file

@ -78,14 +78,12 @@ logger = logging.getLogger(__name__)
# blocks; we use 2 here, leaving headroom for Phase-2 tool caching. # blocks; we use 2 here, leaving headroom for Phase-2 tool caching.
# #
# IMPORTANT: ``index: 0`` (not ``role: system``). The deepagent stack's # IMPORTANT: ``index: 0`` (not ``role: system``). The deepagent stack's
# ``before_agent`` middlewares (priority, tree, memory, file-intent, # ``before_agent`` middlewares (priority, tree, memory, anonymous-doc)
# anonymous-doc) insert ``SystemMessage`` instances into # insert ``SystemMessage`` instances into ``state["messages"]`` that
# ``state["messages"]`` that accumulate across turns. With # accumulate across turns. With ``role: system`` the LiteLLM hook would
# ``role: system`` the LiteLLM hook would tag *every* one of them with # tag *every* one of them with ``cache_control`` and overflow Anthropic's
# ``cache_control`` and overflow Anthropic's 4-block limit. ``index: 0`` # 4-block limit. ``index: 0`` always targets the langchain-prepended
# always targets the langchain-prepended ``request.system_message`` # ``request.system_message``, giving us exactly one stable cache breakpoint.
# (which our ``FlattenSystemMessageMiddleware`` reduces to a single text
# block), giving us exactly one stable cache breakpoint.
_DEFAULT_INJECTION_POINTS: tuple[dict[str, Any], ...] = ( _DEFAULT_INJECTION_POINTS: tuple[dict[str, Any], ...] = (
{"location": "message", "index": 0}, {"location": "message", "index": 0},
{"location": "message", "index": -1}, {"location": "message", "index": -1},

View file

@ -1,344 +0,0 @@
"""Tests for ``FlattenSystemMessageMiddleware``.
The middleware exists to defend against Anthropic's "Found 5 cache_control
blocks" 400 when our deepagent middleware stack stacks 5+ text blocks on
the system message and the OpenRouterAnthropic adapter redistributes
``cache_control`` across all of them. The flattening collapses every
all-text system content list to a single string before the LLM call.
"""
from __future__ import annotations
from typing import Any
from unittest.mock import MagicMock
import pytest
from langchain_core.messages import HumanMessage, SystemMessage
from app.agents.shared.middleware.flatten_system import (
FlattenSystemMessageMiddleware,
_flatten_text_blocks,
_flattened_request,
)
pytestmark = pytest.mark.unit
# ---------------------------------------------------------------------------
# _flatten_text_blocks — pure helper, the heart of the middleware.
# ---------------------------------------------------------------------------
class TestFlattenTextBlocks:
def test_joins_text_blocks_with_double_newline(self) -> None:
blocks = [
{"type": "text", "text": "<surfsense base>"},
{"type": "text", "text": "<filesystem section>"},
{"type": "text", "text": "<skills section>"},
]
assert (
_flatten_text_blocks(blocks)
== "<surfsense base>\n\n<filesystem section>\n\n<skills section>"
)
def test_handles_single_text_block(self) -> None:
blocks = [{"type": "text", "text": "only one"}]
assert _flatten_text_blocks(blocks) == "only one"
def test_handles_empty_list(self) -> None:
assert _flatten_text_blocks([]) == ""
def test_passes_through_bare_string_blocks(self) -> None:
# LangChain content can mix bare strings and dict blocks.
blocks = ["raw string", {"type": "text", "text": "dict block"}]
assert _flatten_text_blocks(blocks) == "raw string\n\ndict block"
def test_returns_none_for_image_block(self) -> None:
# System messages with images are rare — but we never want to
# silently lose the image payload by joining as text.
blocks = [
{"type": "text", "text": "look at this"},
{"type": "image_url", "image_url": {"url": "data:image/png..."}},
]
assert _flatten_text_blocks(blocks) is None
def test_returns_none_for_non_dict_non_str_block(self) -> None:
blocks = [{"type": "text", "text": "hi"}, 42] # type: ignore[list-item]
assert _flatten_text_blocks(blocks) is None
def test_returns_none_when_text_field_missing(self) -> None:
blocks = [{"type": "text"}] # no ``text`` key
assert _flatten_text_blocks(blocks) is None
def test_returns_none_when_text_is_not_string(self) -> None:
blocks = [{"type": "text", "text": ["nested", "list"]}]
assert _flatten_text_blocks(blocks) is None
def test_drops_cache_control_from_inner_blocks(self) -> None:
# The whole point: existing cache_control on inner blocks is
# discarded so LiteLLM's ``cache_control_injection_points`` can
# re-attach exactly one breakpoint after flattening.
blocks = [
{"type": "text", "text": "first"},
{
"type": "text",
"text": "second",
"cache_control": {"type": "ephemeral"},
},
]
flattened = _flatten_text_blocks(blocks)
assert flattened == "first\n\nsecond"
assert "cache_control" not in flattened # type: ignore[operator]
# ---------------------------------------------------------------------------
# _flattened_request — decides when to override and when to no-op.
# ---------------------------------------------------------------------------
def _make_request(system_message: SystemMessage | None) -> Any:
"""Build a minimal ModelRequest stub. We only need .system_message
and .override(system_message=...) the middleware never touches
other fields.
"""
request = MagicMock()
request.system_message = system_message
def override(**kwargs: Any) -> Any:
new_request = MagicMock()
new_request.system_message = kwargs.get(
"system_message", request.system_message
)
new_request.messages = kwargs.get("messages", getattr(request, "messages", []))
new_request.tools = kwargs.get("tools", getattr(request, "tools", []))
return new_request
request.override = override
return request
class TestFlattenedRequest:
def test_collapses_multi_block_system_to_string(self) -> None:
sys = SystemMessage(
content=[
{"type": "text", "text": "<base>"},
{"type": "text", "text": "<todo>"},
{"type": "text", "text": "<filesystem>"},
{"type": "text", "text": "<skills>"},
{"type": "text", "text": "<subagents>"},
]
)
request = _make_request(sys)
flattened = _flattened_request(request)
assert flattened is not None
assert isinstance(flattened.system_message, SystemMessage)
assert flattened.system_message.content == (
"<base>\n\n<todo>\n\n<filesystem>\n\n<skills>\n\n<subagents>"
)
def test_no_op_for_string_content(self) -> None:
sys = SystemMessage(content="already a string")
request = _make_request(sys)
assert _flattened_request(request) is None
def test_no_op_for_single_block_list(self) -> None:
# One block already produces one breakpoint — no need to flatten.
sys = SystemMessage(content=[{"type": "text", "text": "single"}])
request = _make_request(sys)
assert _flattened_request(request) is None
def test_no_op_when_system_message_missing(self) -> None:
request = _make_request(None)
assert _flattened_request(request) is None
def test_no_op_when_list_contains_non_text_block(self) -> None:
sys = SystemMessage(
content=[
{"type": "text", "text": "look"},
{"type": "image_url", "image_url": {"url": "data:..."}},
]
)
request = _make_request(sys)
assert _flattened_request(request) is None
def test_preserves_additional_kwargs_and_metadata(self) -> None:
# Defensive: nothing in the current chain sets these on a system
# message, but losing them silently when something does in the
# future would be a regression. ``name`` in particular is the only
# ``additional_kwargs`` field that ChatLiteLLM's
# ``_convert_message_to_dict`` propagates onto the wire.
sys = SystemMessage(
content=[
{"type": "text", "text": "a"},
{"type": "text", "text": "b"},
],
additional_kwargs={"name": "surfsense_system", "x": 1},
response_metadata={"tokens": 42},
)
sys.id = "sys-msg-1"
request = _make_request(sys)
flattened = _flattened_request(request)
assert flattened is not None
assert flattened.system_message.content == "a\n\nb"
assert flattened.system_message.additional_kwargs == {
"name": "surfsense_system",
"x": 1,
}
assert flattened.system_message.response_metadata == {"tokens": 42}
assert flattened.system_message.id == "sys-msg-1"
def test_idempotent_when_run_twice(self) -> None:
sys = SystemMessage(
content=[
{"type": "text", "text": "a"},
{"type": "text", "text": "b"},
]
)
request = _make_request(sys)
first = _flattened_request(request)
assert first is not None
# Second pass on the already-flattened request should be a no-op.
# We re-wrap in a request stub since the helper inspects
# ``request.system_message.content``.
second_request = _make_request(first.system_message)
assert _flattened_request(second_request) is None
# ---------------------------------------------------------------------------
# Middleware integration — verify the handler sees a flattened request.
# ---------------------------------------------------------------------------
class TestMiddlewareWrap:
@pytest.mark.asyncio
async def test_async_passes_flattened_request_to_handler(self) -> None:
sys = SystemMessage(
content=[
{"type": "text", "text": "alpha"},
{"type": "text", "text": "beta"},
]
)
request = _make_request(sys)
captured: dict[str, Any] = {}
async def handler(req: Any) -> str:
captured["request"] = req
return "ok"
mw = FlattenSystemMessageMiddleware()
result = await mw.awrap_model_call(request, handler)
assert result == "ok"
assert isinstance(captured["request"].system_message, SystemMessage)
assert captured["request"].system_message.content == "alpha\n\nbeta"
@pytest.mark.asyncio
async def test_async_passes_through_when_already_string(self) -> None:
sys = SystemMessage(content="just a string")
request = _make_request(sys)
captured: dict[str, Any] = {}
async def handler(req: Any) -> str:
captured["request"] = req
return "ok"
mw = FlattenSystemMessageMiddleware()
await mw.awrap_model_call(request, handler)
# Same request object: no override happened.
assert captured["request"] is request
def test_sync_passes_flattened_request_to_handler(self) -> None:
sys = SystemMessage(
content=[
{"type": "text", "text": "alpha"},
{"type": "text", "text": "beta"},
]
)
request = _make_request(sys)
captured: dict[str, Any] = {}
def handler(req: Any) -> str:
captured["request"] = req
return "ok"
mw = FlattenSystemMessageMiddleware()
result = mw.wrap_model_call(request, handler)
assert result == "ok"
assert captured["request"].system_message.content == "alpha\n\nbeta"
def test_sync_passes_through_when_no_system_message(self) -> None:
request = _make_request(None)
captured: dict[str, Any] = {}
def handler(req: Any) -> str:
captured["request"] = req
return "ok"
mw = FlattenSystemMessageMiddleware()
mw.wrap_model_call(request, handler)
assert captured["request"] is request
# ---------------------------------------------------------------------------
# Regression guard — pin the worst-case shape that triggered the
# "Found 5" 400 in production. Confirms we collapse 5 blocks to 1 so the
# downstream cache_control_injection_points can only place 1 breakpoint
# on the system message regardless of provider redistribution quirks.
# ---------------------------------------------------------------------------
def test_regression_five_block_system_collapses_to_one_block() -> None:
sys = SystemMessage(
content=[
{"type": "text", "text": "<surfsense base + BASE_AGENT_PROMPT>"},
{"type": "text", "text": "<TodoListMiddleware section>"},
{"type": "text", "text": "<SurfSenseFilesystemMiddleware section>"},
{"type": "text", "text": "<SkillsMiddleware section>"},
{"type": "text", "text": "<SubAgentMiddleware section>"},
]
)
request = _make_request(sys)
flattened = _flattened_request(request)
assert flattened is not None
assert isinstance(flattened.system_message.content, str)
# The exact join doesn't matter for the cache_control accounting —
# only that there is exactly ONE content block when LiteLLM's
# AnthropicCacheControlHook later targets ``role: system``.
assert "<surfsense base" in flattened.system_message.content
assert "<SubAgentMiddleware" in flattened.system_message.content
def test_regression_human_message_not_modified() -> None:
# Sanity: the middleware MUST NOT touch user messages — only the
# system message. Multi-block user content is the path that carries
# image attachments and would lose its image_url block on
# accidental flatten.
sys = SystemMessage(
content=[
{"type": "text", "text": "a"},
{"type": "text", "text": "b"},
]
)
user = HumanMessage(
content=[
{"type": "text", "text": "look at this"},
{"type": "image_url", "image_url": {"url": "data:image/png;base64,..."}},
]
)
request = _make_request(sys)
request.messages = [user]
flattened = _flattened_request(request)
assert flattened is not None
# System flattened to string …
assert isinstance(flattened.system_message.content, str)
# … user message is untouched (the helper does not even look at it).
assert flattened.messages == [user]
assert isinstance(user.content, list)
assert len(user.content) == 2

View file

@ -1,214 +0,0 @@
import pytest
from langchain_core.messages import AIMessage, HumanMessage
from app.agents.shared.middleware.file_intent import (
FileIntentMiddleware,
FileOperationIntent,
_fallback_path,
)
pytestmark = pytest.mark.unit
class _FakeLLM:
def __init__(self, response_text: str):
self._response_text = response_text
async def ainvoke(self, *_args, **_kwargs):
return AIMessage(content=self._response_text)
@pytest.mark.asyncio
async def test_file_write_intent_injects_contract_message():
llm = _FakeLLM(
'{"intent":"file_write","confidence":0.93,"suggested_filename":"ideas.md"}'
)
middleware = FileIntentMiddleware(llm=llm)
state = {
"messages": [HumanMessage(content="Create another random note for me")],
"turn_id": "123:456",
}
result = await middleware.abefore_agent(state, runtime=None) # type: ignore[arg-type]
assert result is not None
contract = result["file_operation_contract"]
assert contract["intent"] == FileOperationIntent.FILE_WRITE.value
assert contract["suggested_path"] == "/ideas.md"
assert contract["turn_id"] == "123:456"
assert any(
"file_operation_contract" in str(msg.content)
for msg in result["messages"]
if hasattr(msg, "content")
)
@pytest.mark.asyncio
async def test_non_write_intent_does_not_inject_contract_message():
llm = _FakeLLM('{"intent":"file_read","confidence":0.88,"suggested_filename":null}')
middleware = FileIntentMiddleware(llm=llm)
original_messages = [HumanMessage(content="Read /notes.md")]
state = {"messages": original_messages, "turn_id": "abc:def"}
result = await middleware.abefore_agent(state, runtime=None) # type: ignore[arg-type]
assert result is not None
assert (
result["file_operation_contract"]["intent"]
== FileOperationIntent.FILE_READ.value
)
assert "messages" not in result
@pytest.mark.asyncio
async def test_file_write_null_filename_uses_semantic_default_path():
llm = _FakeLLM(
'{"intent":"file_write","confidence":0.74,"suggested_filename":null}'
)
middleware = FileIntentMiddleware(llm=llm)
state = {
"messages": [HumanMessage(content="create a random markdown file")],
"turn_id": "turn:1",
}
result = await middleware.abefore_agent(state, runtime=None) # type: ignore[arg-type]
assert result is not None
contract = result["file_operation_contract"]
assert contract["intent"] == FileOperationIntent.FILE_WRITE.value
assert contract["suggested_path"] == "/notes.md"
@pytest.mark.asyncio
async def test_file_write_null_filename_defaults_to_markdown_path():
llm = _FakeLLM(
'{"intent":"file_write","confidence":0.71,"suggested_filename":null}'
)
middleware = FileIntentMiddleware(llm=llm)
state = {
"messages": [HumanMessage(content="create a sample json config file")],
"turn_id": "turn:2",
}
result = await middleware.abefore_agent(state, runtime=None) # type: ignore[arg-type]
assert result is not None
contract = result["file_operation_contract"]
assert contract["intent"] == FileOperationIntent.FILE_WRITE.value
assert contract["suggested_path"] == "/notes.md"
@pytest.mark.asyncio
async def test_file_write_txt_suggestion_is_normalized_to_markdown():
llm = _FakeLLM(
'{"intent":"file_write","confidence":0.82,"suggested_filename":"random.txt"}'
)
middleware = FileIntentMiddleware(llm=llm)
state = {
"messages": [HumanMessage(content="create a random file")],
"turn_id": "turn:3",
}
result = await middleware.abefore_agent(state, runtime=None) # type: ignore[arg-type]
assert result is not None
contract = result["file_operation_contract"]
assert contract["intent"] == FileOperationIntent.FILE_WRITE.value
assert contract["suggested_path"] == "/random.md"
@pytest.mark.asyncio
async def test_file_write_with_suggested_directory_preserves_folder():
llm = _FakeLLM(
'{"intent":"file_write","confidence":0.86,"suggested_filename":"random.md","suggested_directory":"pc backups","suggested_path":null}'
)
middleware = FileIntentMiddleware(llm=llm)
state = {
"messages": [HumanMessage(content="create a random file in pc backups folder")],
"turn_id": "turn:4",
}
result = await middleware.abefore_agent(state, runtime=None) # type: ignore[arg-type]
assert result is not None
contract = result["file_operation_contract"]
assert contract["intent"] == FileOperationIntent.FILE_WRITE.value
assert contract["suggested_path"] == "/pc_backups/random.md"
@pytest.mark.asyncio
async def test_file_write_with_suggested_path_takes_precedence():
llm = _FakeLLM(
'{"intent":"file_write","confidence":0.9,"suggested_filename":"ignored.md","suggested_directory":"docs","suggested_path":"/reports/q2/summary.md"}'
)
middleware = FileIntentMiddleware(llm=llm)
state = {
"messages": [HumanMessage(content="create report")],
"turn_id": "turn:5",
}
result = await middleware.abefore_agent(state, runtime=None) # type: ignore[arg-type]
assert result is not None
contract = result["file_operation_contract"]
assert contract["intent"] == FileOperationIntent.FILE_WRITE.value
assert contract["suggested_path"] == "/reports/q2/summary.md"
@pytest.mark.asyncio
async def test_file_write_infers_directory_from_user_text_when_missing():
llm = _FakeLLM(
'{"intent":"file_write","confidence":0.83,"suggested_filename":"random.md","suggested_directory":null,"suggested_path":null}'
)
middleware = FileIntentMiddleware(llm=llm)
state = {
"messages": [HumanMessage(content="create a random file in pc backups folder")],
"turn_id": "turn:6",
}
result = await middleware.abefore_agent(state, runtime=None) # type: ignore[arg-type]
assert result is not None
contract = result["file_operation_contract"]
assert contract["intent"] == FileOperationIntent.FILE_WRITE.value
assert contract["suggested_path"] == "/pc_backups/random.md"
def test_fallback_path_normalizes_windows_slashes() -> None:
resolved = _fallback_path(
suggested_filename="summary.md",
suggested_path=r"\reports\q2\summary.md",
user_text="create report",
)
assert resolved == "/reports/q2/summary.md"
def test_fallback_path_normalizes_windows_drive_path() -> None:
resolved = _fallback_path(
suggested_filename=None,
suggested_path=r"C:\Users\anish\notes\todo.md",
user_text="create note",
)
assert resolved == "/C/Users/anish/notes/todo.md"
def test_fallback_path_normalizes_mixed_separators_and_duplicate_slashes() -> None:
resolved = _fallback_path(
suggested_filename="summary.md",
suggested_path=r"\\reports\\q2//summary.md",
user_text="create report",
)
assert resolved == "/reports/q2/summary.md"
def test_fallback_path_keeps_posix_style_absolute_path_for_linux_and_macos() -> None:
resolved = _fallback_path(
suggested_filename=None,
suggested_path="/var/log/surfsense/notes.md",
user_text="create note",
)
assert resolved == "/var/log/surfsense/notes.md"

View file

@ -10,7 +10,7 @@ from app.agents.multi_agent_chat.shared.middleware.filesystem.backends.document_
) )
from app.agents.shared.middleware.knowledge_search import ( from app.agents.shared.middleware.knowledge_search import (
KBSearchPlan, KBSearchPlan,
KnowledgeBaseSearchMiddleware, KnowledgePriorityMiddleware,
_normalize_optional_date_range, _normalize_optional_date_range,
_parse_kb_search_plan_response, _parse_kb_search_plan_response,
_render_recent_conversation, _render_recent_conversation,
@ -203,7 +203,7 @@ class FakeBudgetLLM:
return sum(len(msg.get("content", "")) for msg in messages) return sum(len(msg.get("content", "")) for msg in messages)
class TestKnowledgeBaseSearchMiddlewarePlanner: class TestKnowledgePriorityMiddlewarePlanner:
@pytest.fixture(autouse=True) @pytest.fixture(autouse=True)
def _disable_planner_runnable(self, monkeypatch): def _disable_planner_runnable(self, monkeypatch):
# ``FakeLLM`` is a duck-typed mock; ``create_agent`` (used when the # ``FakeLLM`` is a duck-typed mock; ``create_agent`` (used when the
@ -273,7 +273,7 @@ class TestKnowledgeBaseSearchMiddlewarePlanner:
} }
) )
) )
middleware = KnowledgeBaseSearchMiddleware(llm=llm, search_space_id=37) middleware = KnowledgePriorityMiddleware(llm=llm, search_space_id=37)
result = await middleware.abefore_agent( result = await middleware.abefore_agent(
{ {
@ -307,7 +307,7 @@ class TestKnowledgeBaseSearchMiddlewarePlanner:
fake_search_knowledge_base, fake_search_knowledge_base,
) )
middleware = KnowledgeBaseSearchMiddleware( middleware = KnowledgePriorityMiddleware(
llm=FakeLLM("not json"), llm=FakeLLM("not json"),
search_space_id=37, search_space_id=37,
) )
@ -336,7 +336,7 @@ class TestKnowledgeBaseSearchMiddlewarePlanner:
fake_search_knowledge_base, fake_search_knowledge_base,
) )
middleware = KnowledgeBaseSearchMiddleware( middleware = KnowledgePriorityMiddleware(
llm=FakeLLM( llm=FakeLLM(
json.dumps( json.dumps(
{ {
@ -395,7 +395,7 @@ class TestKnowledgeBaseSearchMiddlewarePlanner:
} }
) )
) )
middleware = KnowledgeBaseSearchMiddleware(llm=llm, search_space_id=42) middleware = KnowledgePriorityMiddleware(llm=llm, search_space_id=42)
result = await middleware.abefore_agent( result = await middleware.abefore_agent(
{"messages": [HumanMessage(content="what's my latest file?")]}, {"messages": [HumanMessage(content="what's my latest file?")]},
@ -442,7 +442,7 @@ class TestKnowledgeBaseSearchMiddlewarePlanner:
} }
) )
) )
middleware = KnowledgeBaseSearchMiddleware(llm=llm, search_space_id=42) middleware = KnowledgePriorityMiddleware(llm=llm, search_space_id=42)
await middleware.abefore_agent( await middleware.abefore_agent(
{"messages": [HumanMessage(content="find the quarterly revenue report")]}, {"messages": [HumanMessage(content="find the quarterly revenue report")]},
@ -559,7 +559,7 @@ class TestKnowledgePriorityMentionDrain:
fake_search_knowledge_base, fake_search_knowledge_base,
) )
middleware = KnowledgeBaseSearchMiddleware( middleware = KnowledgePriorityMiddleware(
llm=self._planner_llm(), llm=self._planner_llm(),
search_space_id=42, search_space_id=42,
mentioned_document_ids=[1, 2, 3], mentioned_document_ids=[1, 2, 3],
@ -609,7 +609,7 @@ class TestKnowledgePriorityMentionDrain:
# Simulate a cached middleware instance whose closure was seeded # Simulate a cached middleware instance whose closure was seeded
# by a previous turn's cache-miss build (mentions=[1,2,3]). # by a previous turn's cache-miss build (mentions=[1,2,3]).
middleware = KnowledgeBaseSearchMiddleware( middleware = KnowledgePriorityMiddleware(
llm=self._planner_llm(), llm=self._planner_llm(),
search_space_id=42, search_space_id=42,
mentioned_document_ids=[1, 2, 3], mentioned_document_ids=[1, 2, 3],
@ -652,7 +652,7 @@ class TestKnowledgePriorityMentionDrain:
fake_search_knowledge_base, fake_search_knowledge_base,
) )
middleware = KnowledgeBaseSearchMiddleware( middleware = KnowledgePriorityMiddleware(
llm=self._planner_llm(), llm=self._planner_llm(),
search_space_id=42, search_space_id=42,
mentioned_document_ids=[7, 8], mentioned_document_ids=[7, 8],