fix(memory): prevent file upload events from persisting in long-term memory (#971)

* fix(memory): prevent file upload events from persisting in long-term memory

Uploaded files are session-scoped and unavailable in future sessions.
Previously, upload interactions were recorded in memory, causing the
agent to search for non-existent files in subsequent conversations.

Changes:
- memory_middleware: skip human messages containing <uploaded_files>
  and their paired AI responses from the memory queue
- updater: post-process generated memory to strip upload mentions
  before saving to file
- prompt: instruct the memory LLM to ignore file upload events

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix(memory): address Copilot review feedback on upload filtering

- memory_middleware: strip <uploaded_files> block from human messages
  instead of dropping the entire turn; only skip the turn (and paired
  AI response) when nothing remains after stripping
- updater: narrow the upload-scrubbing regex to explicit upload events
  (avoids false-positive removal of "User works with CSV files" etc.);
  also filter upload-event facts from the facts array
- prompt: move `import re` to module scope; skip upload-only human
  messages (empty after stripping) rather than appending "User: "

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* fix(memory): allow optional words between 'upload' and 'file' in scrub regex

The previous pattern required 'uploading file' with no intervening words,
so 'uploading a test file' was not matched and leaked into long-term memory.
Allow up to 3 modifier words between the verb and noun (e.g. 'uploading a
test file', 'uploaded the attachment').

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

* test(memory): add unit tests for upload filtering in memory pipeline

Covers _filter_messages_for_memory and _strip_upload_mentions_from_memory
per Copilot review suggestion.  15 test cases verify:

- Upload-only turns (and paired AI responses) are excluded from memory queue
- User's real question is preserved when combined with an upload block
- Upload file paths are never present in filtered message content
- Intermediate tool messages are always excluded
- Multi-turn conversations: only the upload turn is dropped
- Multimodal (list-content) human messages are handled
- Upload-event sentences are removed from summaries and facts
- Legitimate file-related facts (CSV preferences, PDF exports) are preserved
- "uploading a test file" (words between verb and noun) is caught by regex

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
This commit is contained in:
DanielWalnut
2026-03-05 11:14:34 +08:00
committed by GitHub
parent 6ac0042cfe
commit 3ada4f98b1
4 changed files with 336 additions and 5 deletions

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@@ -1,5 +1,6 @@
"""Prompt templates for memory update and injection."""
import re
from typing import Any
try:
@@ -108,6 +109,9 @@ Important Rules:
- For history sections, integrate new information chronologically into appropriate time period
- Preserve technical accuracy - keep exact names of technologies, companies, projects
- Focus on information useful for future interactions and personalization
- IMPORTANT: Do NOT record file upload events in memory. Uploaded files are
session-specific and ephemeral — they will not be accessible in future sessions.
Recording upload events causes confusion in subsequent conversations.
Return ONLY valid JSON, no explanation or markdown."""
@@ -249,6 +253,16 @@ def format_conversation_for_update(messages: list[Any]) -> str:
text_parts = [p.get("text", "") for p in content if isinstance(p, dict) and "text" in p]
content = " ".join(text_parts) if text_parts else str(content)
# Strip uploaded_files tags from human messages to avoid persisting
# ephemeral file path info into long-term memory. Skip the turn entirely
# when nothing remains after stripping (upload-only message).
if role == "human":
content = re.sub(
r"<uploaded_files>[\s\S]*?</uploaded_files>\n*", "", str(content)
).strip()
if not content:
continue
# Truncate very long messages
if len(str(content)) > 1000:
content = str(content)[:1000] + "..."

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@@ -1,6 +1,7 @@
"""Memory updater for reading, writing, and updating memory data."""
import json
import re
import uuid
from datetime import datetime
from pathlib import Path
@@ -135,6 +136,47 @@ def _load_memory_from_file(agent_name: str | None = None) -> dict[str, Any]:
return _create_empty_memory()
# Matches sentences that describe a file-upload *event* rather than general
# file-related work. Deliberately narrow to avoid removing legitimate facts
# such as "User works with CSV files" or "prefers PDF export".
_UPLOAD_SENTENCE_RE = re.compile(
r"[^.!?]*\b(?:"
r"upload(?:ed|ing)?(?:\s+\w+){0,3}\s+(?:file|files?|document|documents?|attachment|attachments?)"
r"|file\s+upload"
r"|/mnt/user-data/uploads/"
r"|<uploaded_files>"
r")[^.!?]*[.!?]?\s*",
re.IGNORECASE,
)
def _strip_upload_mentions_from_memory(memory_data: dict[str, Any]) -> dict[str, Any]:
"""Remove sentences about file uploads from all memory summaries and facts.
Uploaded files are session-scoped; persisting upload events in long-term
memory causes the agent to search for non-existent files in future sessions.
"""
# Scrub summaries in user/history sections
for section in ("user", "history"):
section_data = memory_data.get(section, {})
for _key, val in section_data.items():
if isinstance(val, dict) and "summary" in val:
cleaned = _UPLOAD_SENTENCE_RE.sub("", val["summary"]).strip()
cleaned = re.sub(r" +", " ", cleaned)
val["summary"] = cleaned
# Also remove any facts that describe upload events
facts = memory_data.get("facts", [])
if facts:
memory_data["facts"] = [
f
for f in facts
if not _UPLOAD_SENTENCE_RE.search(f.get("content", ""))
]
return memory_data
def _save_memory_to_file(memory_data: dict[str, Any], agent_name: str | None = None) -> bool:
"""Save memory data to file and update cache.
@@ -244,6 +286,12 @@ class MemoryUpdater:
# Apply updates
updated_memory = self._apply_updates(current_memory, update_data, thread_id)
# Strip file-upload mentions from all summaries before saving.
# Uploaded files are session-scoped and won't exist in future sessions,
# so recording upload events in long-term memory causes the agent to
# try (and fail) to locate those files in subsequent conversations.
updated_memory = _strip_upload_mentions_from_memory(updated_memory)
# Save
return _save_memory_to_file(updated_memory, agent_name)

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@@ -1,5 +1,6 @@
"""Middleware for memory mechanism."""
import re
from typing import Any, override
from langchain.agents import AgentState
@@ -22,10 +23,16 @@ def _filter_messages_for_memory(messages: list[Any]) -> list[Any]:
This filters out:
- Tool messages (intermediate tool call results)
- AI messages with tool_calls (intermediate steps, not final responses)
- The <uploaded_files> block injected by UploadsMiddleware into human messages
(file paths are session-scoped and must not persist in long-term memory).
The user's actual question is preserved; only turns whose content is entirely
the upload block (nothing remains after stripping) are dropped along with
their paired assistant response.
Only keeps:
- Human messages (user input)
- AI messages without tool_calls (final assistant responses)
- Human messages (with the ephemeral upload block removed)
- AI messages without tool_calls (final assistant responses), unless the
paired human turn was upload-only and had no real user text.
Args:
messages: List of all conversation messages.
@@ -33,17 +40,47 @@ def _filter_messages_for_memory(messages: list[Any]) -> list[Any]:
Returns:
Filtered list containing only user inputs and final assistant responses.
"""
_UPLOAD_BLOCK_RE = re.compile(
r"<uploaded_files>[\s\S]*?</uploaded_files>\n*", re.IGNORECASE
)
filtered = []
skip_next_ai = False
for msg in messages:
msg_type = getattr(msg, "type", None)
if msg_type == "human":
# Always keep user messages
filtered.append(msg)
content = getattr(msg, "content", "")
if isinstance(content, list):
content = " ".join(
p.get("text", "") for p in content if isinstance(p, dict)
)
content_str = str(content)
if "<uploaded_files>" in content_str:
# Strip the ephemeral upload block; keep the user's real question.
stripped = _UPLOAD_BLOCK_RE.sub("", content_str).strip()
if not stripped:
# Nothing left — the entire turn was upload bookkeeping;
# skip it and the paired assistant response.
skip_next_ai = True
continue
# Rebuild the message with cleaned content so the user's question
# is still available for memory summarisation.
from copy import copy
clean_msg = copy(msg)
clean_msg.content = stripped
filtered.append(clean_msg)
skip_next_ai = False
else:
filtered.append(msg)
skip_next_ai = False
elif msg_type == "ai":
# Only keep AI messages that are final responses (no tool_calls)
tool_calls = getattr(msg, "tool_calls", None)
if not tool_calls:
if skip_next_ai:
skip_next_ai = False
continue
filtered.append(msg)
# Skip tool messages and AI messages with tool_calls

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@@ -0,0 +1,232 @@
"""Tests for upload-event filtering in the memory pipeline.
Covers two functions introduced to prevent ephemeral file-upload context from
persisting in long-term memory:
- _filter_messages_for_memory (memory_middleware)
- _strip_upload_mentions_from_memory (updater)
"""
from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
from src.agents.memory.updater import _strip_upload_mentions_from_memory
from src.agents.middlewares.memory_middleware import _filter_messages_for_memory
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
_UPLOAD_BLOCK = (
"<uploaded_files>\n"
"The following files have been uploaded and are available for use:\n\n"
"- filename: secret.txt\n"
" path: /mnt/user-data/uploads/abc123/secret.txt\n"
" size: 42 bytes\n"
"</uploaded_files>"
)
def _human(text: str) -> HumanMessage:
return HumanMessage(content=text)
def _ai(text: str, tool_calls=None) -> AIMessage:
msg = AIMessage(content=text)
if tool_calls:
msg.tool_calls = tool_calls
return msg
# ===========================================================================
# _filter_messages_for_memory
# ===========================================================================
class TestFilterMessagesForMemory:
# --- upload-only turns are excluded ---
def test_upload_only_turn_is_excluded(self):
"""A human turn containing only <uploaded_files> (no real question)
and its paired AI response must both be dropped."""
msgs = [
_human(_UPLOAD_BLOCK),
_ai("I have read the file. It says: Hello."),
]
result = _filter_messages_for_memory(msgs)
assert result == []
def test_upload_with_real_question_preserves_question(self):
"""When the user asks a question alongside an upload, the question text
must reach the memory queue (upload block stripped, AI response kept)."""
combined = _UPLOAD_BLOCK + "\n\nWhat does this file contain?"
msgs = [
_human(combined),
_ai("The file contains: Hello DeerFlow."),
]
result = _filter_messages_for_memory(msgs)
assert len(result) == 2
human_result = result[0]
assert "<uploaded_files>" not in human_result.content
assert "What does this file contain?" in human_result.content
assert result[1].content == "The file contains: Hello DeerFlow."
# --- non-upload turns pass through unchanged ---
def test_plain_conversation_passes_through(self):
msgs = [
_human("What is the capital of France?"),
_ai("The capital of France is Paris."),
]
result = _filter_messages_for_memory(msgs)
assert len(result) == 2
assert result[0].content == "What is the capital of France?"
assert result[1].content == "The capital of France is Paris."
def test_tool_messages_are_excluded(self):
"""Intermediate tool messages must never reach memory."""
msgs = [
_human("Search for something"),
_ai("Calling search tool", tool_calls=[{"name": "search", "id": "1", "args": {}}]),
ToolMessage(content="Search results", tool_call_id="1"),
_ai("Here are the results."),
]
result = _filter_messages_for_memory(msgs)
human_msgs = [m for m in result if m.type == "human"]
ai_msgs = [m for m in result if m.type == "ai"]
assert len(human_msgs) == 1
assert len(ai_msgs) == 1
assert ai_msgs[0].content == "Here are the results."
def test_multi_turn_with_upload_in_middle(self):
"""Only the upload turn is dropped; surrounding non-upload turns survive."""
msgs = [
_human("Hello, how are you?"),
_ai("I'm doing well, thank you!"),
_human(_UPLOAD_BLOCK), # upload-only → dropped
_ai("I read the uploaded file."), # paired AI → dropped
_human("What is 2 + 2?"),
_ai("4"),
]
result = _filter_messages_for_memory(msgs)
human_contents = [m.content for m in result if m.type == "human"]
ai_contents = [m.content for m in result if m.type == "ai"]
assert "Hello, how are you?" in human_contents
assert "What is 2 + 2?" in human_contents
assert _UPLOAD_BLOCK not in human_contents
assert "I'm doing well, thank you!" in ai_contents
assert "4" in ai_contents
# The upload-paired AI response must NOT appear
assert "I read the uploaded file." not in ai_contents
def test_multimodal_content_list_handled(self):
"""Human messages with list-style content (multimodal) are handled."""
msg = HumanMessage(content=[
{"type": "text", "text": _UPLOAD_BLOCK},
])
msgs = [msg, _ai("Done.")]
result = _filter_messages_for_memory(msgs)
assert result == []
def test_file_path_not_in_filtered_content(self):
"""After filtering, no upload file path should appear in any message."""
combined = _UPLOAD_BLOCK + "\n\nSummarise the file please."
msgs = [_human(combined), _ai("It says hello.")]
result = _filter_messages_for_memory(msgs)
all_content = " ".join(
m.content for m in result if isinstance(m.content, str)
)
assert "/mnt/user-data/uploads/" not in all_content
assert "<uploaded_files>" not in all_content
# ===========================================================================
# _strip_upload_mentions_from_memory
# ===========================================================================
class TestStripUploadMentionsFromMemory:
def _make_memory(self, summary: str, facts: list[dict] | None = None) -> dict:
return {
"user": {"topOfMind": {"summary": summary}},
"history": {"recentMonths": {"summary": ""}},
"facts": facts or [],
}
# --- summaries ---
def test_upload_event_sentence_removed_from_summary(self):
mem = self._make_memory(
"User is interested in AI. "
"User uploaded a test file for verification purposes. "
"User prefers concise answers."
)
result = _strip_upload_mentions_from_memory(mem)
summary = result["user"]["topOfMind"]["summary"]
assert "uploaded a test file" not in summary
assert "User is interested in AI" in summary
assert "User prefers concise answers" in summary
def test_upload_path_sentence_removed_from_summary(self):
mem = self._make_memory(
"User uses Python. "
"User uploaded file to /mnt/user-data/uploads/tid/data.csv. "
"User likes clean code."
)
result = _strip_upload_mentions_from_memory(mem)
summary = result["user"]["topOfMind"]["summary"]
assert "/mnt/user-data/uploads/" not in summary
assert "User uses Python" in summary
def test_legitimate_csv_mention_is_preserved(self):
"""'User works with CSV files' must NOT be deleted — it's not an upload event."""
mem = self._make_memory("User regularly works with CSV files for data analysis.")
result = _strip_upload_mentions_from_memory(mem)
assert "CSV files" in result["user"]["topOfMind"]["summary"]
def test_pdf_export_preference_preserved(self):
"""'Prefers PDF export' is a legitimate preference, not an upload event."""
mem = self._make_memory("User prefers PDF export for reports.")
result = _strip_upload_mentions_from_memory(mem)
assert "PDF export" in result["user"]["topOfMind"]["summary"]
def test_uploading_a_test_file_removed(self):
"""'uploading a test file' (with intervening words) must be caught."""
mem = self._make_memory(
"User conducted a hands-on test by uploading a test file titled "
"'test_deerflow_memory_bug.txt'. User is also learning Python."
)
result = _strip_upload_mentions_from_memory(mem)
summary = result["user"]["topOfMind"]["summary"]
assert "test_deerflow_memory_bug.txt" not in summary
assert "uploading a test file" not in summary
# --- facts ---
def test_upload_fact_removed_from_facts(self):
facts = [
{"content": "User uploaded a file titled secret.txt", "category": "behavior"},
{"content": "User prefers dark mode", "category": "preference"},
{"content": "User is uploading document attachments regularly", "category": "behavior"},
]
mem = self._make_memory("summary", facts=facts)
result = _strip_upload_mentions_from_memory(mem)
remaining = [f["content"] for f in result["facts"]]
assert "User prefers dark mode" in remaining
assert not any("uploaded a file" in c for c in remaining)
assert not any("uploading document" in c for c in remaining)
def test_non_upload_facts_preserved(self):
facts = [
{"content": "User graduated from Peking University", "category": "context"},
{"content": "User prefers Python over JavaScript", "category": "preference"},
]
mem = self._make_memory("", facts=facts)
result = _strip_upload_mentions_from_memory(mem)
assert len(result["facts"]) == 2
def test_empty_memory_handled_gracefully(self):
mem = {"user": {}, "history": {}, "facts": []}
result = _strip_upload_mentions_from_memory(mem)
assert result == {"user": {}, "history": {}, "facts": []}