#!/usr/bin/env python3 """ Memory Tool Module - Persistent Curated Memory Provides bounded, file-backed memory that persists across sessions. Two stores: - MEMORY.md: agent's personal notes and observations (environment facts, project conventions, tool quirks, things learned) - USER.md: what the agent knows about the user (preferences, communication style, expectations, workflow habits) Both are injected into the system prompt as a frozen snapshot at session start. Mid-session writes update files on disk immediately (durable) but do NOT change the system prompt -- this preserves the prefix cache for the entire session. The snapshot refreshes on the next session start. Entry delimiter: § (section sign). Entries can be multiline. Character limits (not tokens) because char counts are model-independent. Design: - Single `memory` tool with action parameter: add, replace, remove, read - replace/remove use short unique substring matching (not full text or IDs) - Behavioral guidance lives in the tool schema description - Frozen snapshot pattern: system prompt is stable, tool responses show live state """ import json import logging import os import tempfile import time from contextlib import contextmanager from pathlib import Path from hermes_constants import get_hermes_home from typing import Dict, Any, List, Optional from utils import atomic_replace # fcntl is Unix-only; on Windows use msvcrt for file locking msvcrt = None try: import fcntl except ImportError: fcntl = None try: import msvcrt except ImportError: pass logger = logging.getLogger(__name__) # Where memory files live — resolved dynamically so profile overrides # (HERMES_HOME env var changes) are always respected. The old module-level # constant was cached at import time and could go stale if a profile switch # happened after the first import. def get_memory_dir() -> Path: """Return the profile-scoped memories directory.""" return get_hermes_home() / "memories" ENTRY_DELIMITER = "\n§\n" # --------------------------------------------------------------------------- # Memory content scanning — lightweight check for injection/exfiltration # in content that gets injected into the system prompt. # # Patterns live in ``tools/threat_patterns.py`` — the single source of truth # shared with the context-file scanner and the tool-result delimiter system. # Memory uses the "strict" scope (broadest pattern set) because: # - memory entries are user-curated; the user can rewrite a flagged entry # - memory enters the system prompt as a FROZEN snapshot, so a poisoned # entry persists for the entire session and across sessions until # explicitly removed. # --------------------------------------------------------------------------- from tools.threat_patterns import first_threat_message as _first_threat_message def _scan_memory_content(content: str) -> Optional[str]: """Scan memory content for injection/exfil patterns. Returns error string if blocked.""" return _first_threat_message(content, scope="strict") def _drift_error(path: "Path", bak_path: str) -> Dict[str, Any]: """Build the error dict returned when external drift is detected. The on-disk memory file contains content that wouldn't round-trip through the tool's parser/serializer — flushing would discard the appended/edited content from a patch tool, shell append, manual edit, or sister-session write. We refuse the mutation, point the operator at the .bak. snapshot we took, and tell them what to do next. """ return { "success": False, "error": ( f"Refusing to write {path.name}: file on disk has content that " f"wouldn't round-trip through the memory tool (likely added by " f"the patch tool, a shell append, a manual edit, or a " f"concurrent session). A snapshot was saved to {bak_path}. " f"Resolve the drift first — either rewrite the file as a clean " f"§-delimited list of entries, or move the extra content out — " f"then retry. This guard exists to prevent silent data loss " f"(issue #26045)." ), "drift_backup": bak_path, "remediation": ( "Open the .bak file, integrate the missing entries into the " "memory tool one at a time via memory(action=add, content=...), " "then remove or rewrite the original file to a clean state." ), } class MemoryStore: """ Bounded curated memory with file persistence. One instance per AIAgent. Maintains two parallel states: - _system_prompt_snapshot: frozen at load time, used for system prompt injection. Never mutated mid-session. Keeps prefix cache stable. - memory_entries / user_entries: live state, mutated by tool calls, persisted to disk. Tool responses always reflect this live state. """ def __init__(self, memory_char_limit: int = 2200, user_char_limit: int = 1375): self.memory_entries: List[str] = [] self.user_entries: List[str] = [] self.memory_char_limit = memory_char_limit self.user_char_limit = user_char_limit # Frozen snapshot for system prompt -- set once at load_from_disk() self._system_prompt_snapshot: Dict[str, str] = {"memory": "", "user": ""} def load_from_disk(self): """Load entries from MEMORY.md and USER.md, capture system prompt snapshot. The frozen snapshot is what enters the system prompt. We scan each entry for injection/promptware patterns at snapshot-build time — ANY hit replaces the entry text in the snapshot with a placeholder like ``[BLOCKED: …]``, so a poisoned-on-disk memory file (supply chain, compromised tool, sister-session write) cannot inject into the system prompt. The live ``memory_entries`` / ``user_entries`` lists keep the original text so the user can still SEE poisoned entries via ``memory(action=read)`` and remove them — silently dropping them would hide the attack from the user. Scanning is deterministic from disk bytes, so the snapshot remains stable for the entire session (prefix-cache invariant holds). """ mem_dir = get_memory_dir() mem_dir.mkdir(parents=True, exist_ok=True) self.memory_entries = self._read_file(mem_dir / "MEMORY.md") self.user_entries = self._read_file(mem_dir / "USER.md") # Deduplicate entries (preserves order, keeps first occurrence) self.memory_entries = list(dict.fromkeys(self.memory_entries)) self.user_entries = list(dict.fromkeys(self.user_entries)) # Sanitize entries for the system-prompt snapshot only. Live state # (memory_entries / user_entries) keeps the raw text so the user # can see + remove poisoned entries via the memory tool. sanitized_memory = self._sanitize_entries_for_snapshot(self.memory_entries, "MEMORY.md") sanitized_user = self._sanitize_entries_for_snapshot(self.user_entries, "USER.md") # Capture frozen snapshot for system prompt injection self._system_prompt_snapshot = { "memory": self._render_block("memory", sanitized_memory), "user": self._render_block("user", sanitized_user), } @staticmethod def _sanitize_entries_for_snapshot(entries: List[str], filename: str) -> List[str]: """Return ``entries`` with any threat-matching entry replaced by a placeholder. Each entry is scanned with the shared threat-pattern library at the ``"strict"`` scope (same as memory writes). On match, the entry is replaced in the returned list with ``"[BLOCKED: entry contained threat pattern: . Removed from system prompt.]"`` — the placeholder enters the snapshot, the original entry stays in live state for the user to inspect and delete. Empty or already-block-marker entries pass through unchanged. """ from tools.threat_patterns import scan_for_threats sanitized: List[str] = [] for entry in entries: if not entry or entry.startswith("[BLOCKED:"): sanitized.append(entry) continue findings = scan_for_threats(entry, scope="strict") if findings: logger.warning( "Memory entry from %s blocked at load time: %s", filename, ", ".join(findings), ) sanitized.append( f"[BLOCKED: {filename} entry contained threat pattern(s): " f"{', '.join(findings)}. Removed from system prompt; " f"use memory(action=read) to inspect and memory(action=remove) " f"to delete the original.]" ) else: sanitized.append(entry) return sanitized @staticmethod @contextmanager def _file_lock(path: Path): """Acquire an exclusive file lock for read-modify-write safety. Uses a separate .lock file so the memory file itself can still be atomically replaced via os.replace(). """ lock_path = path.with_suffix(path.suffix + ".lock") lock_path.parent.mkdir(parents=True, exist_ok=True) if fcntl is None and msvcrt is None: yield return fd = open(lock_path, "a+", encoding="utf-8") try: if fcntl: fcntl.flock(fd, fcntl.LOCK_EX) else: fd.seek(0) msvcrt.locking(fd.fileno(), msvcrt.LK_LOCK, 1) yield finally: if fcntl: try: fcntl.flock(fd, fcntl.LOCK_UN) except (OSError, IOError): pass elif msvcrt: try: fd.seek(0) msvcrt.locking(fd.fileno(), msvcrt.LK_UNLCK, 1) except (OSError, IOError): pass fd.close() @staticmethod def _path_for(target: str) -> Path: mem_dir = get_memory_dir() if target == "user": return mem_dir / "USER.md" return mem_dir / "MEMORY.md" def _reload_target(self, target: str) -> Optional[str]: """Re-read entries from disk into in-memory state. Called under file lock to get the latest state before mutating. Returns the backup path if external drift was detected (the on-disk file contains content that wouldn't round-trip through our parser/serializer, OR an entry larger than the store's char limit). When drift is detected the caller must abort the mutation — flushing would discard the un-roundtrippable content. Returns None on clean reload. """ path = self._path_for(target) bak = self._detect_external_drift(target) fresh = self._read_file(path) fresh = list(dict.fromkeys(fresh)) # deduplicate self._set_entries(target, fresh) return bak def save_to_disk(self, target: str): """Persist entries to the appropriate file. Called after every mutation.""" get_memory_dir().mkdir(parents=True, exist_ok=True) self._write_file(self._path_for(target), self._entries_for(target)) def _entries_for(self, target: str) -> List[str]: if target == "user": return self.user_entries return self.memory_entries def _set_entries(self, target: str, entries: List[str]): if target == "user": self.user_entries = entries else: self.memory_entries = entries def _char_count(self, target: str) -> int: entries = self._entries_for(target) if not entries: return 0 return len(ENTRY_DELIMITER.join(entries)) def _char_limit(self, target: str) -> int: if target == "user": return self.user_char_limit return self.memory_char_limit def add(self, target: str, content: str) -> Dict[str, Any]: """Append a new entry. Returns error if it would exceed the char limit.""" content = content.strip() if not content: return {"success": False, "error": "Content cannot be empty."} # Scan for injection/exfiltration before accepting scan_error = _scan_memory_content(content) if scan_error: return {"success": False, "error": scan_error} with self._file_lock(self._path_for(target)): # Re-read from disk under lock to pick up writes from other sessions. # If external drift was detected, the file was backed up to .bak. # — refuse the mutation so we don't clobber the un-roundtrippable # content the patch tool / shell append / sister session wrote. bak = self._reload_target(target) if bak: return _drift_error(self._path_for(target), bak) entries = self._entries_for(target) limit = self._char_limit(target) # Reject exact duplicates if content in entries: return self._success_response(target, "Entry already exists (no duplicate added).") # Calculate what the new total would be new_entries = entries + [content] new_total = len(ENTRY_DELIMITER.join(new_entries)) if new_total > limit: current = self._char_count(target) return { "success": False, "error": ( f"Memory at {current:,}/{limit:,} chars. " f"Adding this entry ({len(content)} chars) would exceed the limit. " f"Replace or remove existing entries first." ), "current_entries": entries, "usage": f"{current:,}/{limit:,}", } entries.append(content) self._set_entries(target, entries) self.save_to_disk(target) return self._success_response(target, "Entry added.") def replace(self, target: str, old_text: str, new_content: str) -> Dict[str, Any]: """Find entry containing old_text substring, replace it with new_content.""" old_text = old_text.strip() new_content = new_content.strip() if not old_text: return {"success": False, "error": "old_text cannot be empty."} if not new_content: return {"success": False, "error": "new_content cannot be empty. Use 'remove' to delete entries."} # Scan replacement content for injection/exfiltration scan_error = _scan_memory_content(new_content) if scan_error: return {"success": False, "error": scan_error} with self._file_lock(self._path_for(target)): bak = self._reload_target(target) if bak: return _drift_error(self._path_for(target), bak) entries = self._entries_for(target) matches = [(i, e) for i, e in enumerate(entries) if old_text in e] if not matches: return {"success": False, "error": f"No entry matched '{old_text}'."} if len(matches) > 1: # If all matches are identical (exact duplicates), operate on the first one unique_texts = {e for _, e in matches} if len(unique_texts) > 1: previews = [e[:80] + ("..." if len(e) > 80 else "") for _, e in matches] return { "success": False, "error": f"Multiple entries matched '{old_text}'. Be more specific.", "matches": previews, } # All identical -- safe to replace just the first idx = matches[0][0] limit = self._char_limit(target) # Check that replacement doesn't blow the budget test_entries = entries.copy() test_entries[idx] = new_content new_total = len(ENTRY_DELIMITER.join(test_entries)) if new_total > limit: return { "success": False, "error": ( f"Replacement would put memory at {new_total:,}/{limit:,} chars. " f"Shorten the new content or remove other entries first." ), } entries[idx] = new_content self._set_entries(target, entries) self.save_to_disk(target) return self._success_response(target, "Entry replaced.") def remove(self, target: str, old_text: str) -> Dict[str, Any]: """Remove the entry containing old_text substring.""" old_text = old_text.strip() if not old_text: return {"success": False, "error": "old_text cannot be empty."} with self._file_lock(self._path_for(target)): bak = self._reload_target(target) if bak: return _drift_error(self._path_for(target), bak) entries = self._entries_for(target) matches = [(i, e) for i, e in enumerate(entries) if old_text in e] if not matches: return {"success": False, "error": f"No entry matched '{old_text}'."} if len(matches) > 1: # If all matches are identical (exact duplicates), remove the first one unique_texts = {e for _, e in matches} if len(unique_texts) > 1: previews = [e[:80] + ("..." if len(e) > 80 else "") for _, e in matches] return { "success": False, "error": f"Multiple entries matched '{old_text}'. Be more specific.", "matches": previews, } # All identical -- safe to remove just the first idx = matches[0][0] entries.pop(idx) self._set_entries(target, entries) self.save_to_disk(target) return self._success_response(target, "Entry removed.") def format_for_system_prompt(self, target: str) -> Optional[str]: """ Return the frozen snapshot for system prompt injection. This returns the state captured at load_from_disk() time, NOT the live state. Mid-session writes do not affect this. This keeps the system prompt stable across all turns, preserving the prefix cache. Returns None if the snapshot is empty (no entries at load time). """ block = self._system_prompt_snapshot.get(target, "") return block if block else None # -- Internal helpers -- def _success_response(self, target: str, message: str = None) -> Dict[str, Any]: entries = self._entries_for(target) current = self._char_count(target) limit = self._char_limit(target) pct = min(100, int((current / limit) * 100)) if limit > 0 else 0 resp = { "success": True, "target": target, "entries": entries, "usage": f"{pct}% — {current:,}/{limit:,} chars", "entry_count": len(entries), } if message: resp["message"] = message return resp def _render_block(self, target: str, entries: List[str]) -> str: """Render a system prompt block with header and usage indicator.""" if not entries: return "" limit = self._char_limit(target) content = ENTRY_DELIMITER.join(entries) current = len(content) pct = min(100, int((current / limit) * 100)) if limit > 0 else 0 if target == "user": header = f"USER PROFILE (who the user is) [{pct}% — {current:,}/{limit:,} chars]" else: header = f"MEMORY (your personal notes) [{pct}% — {current:,}/{limit:,} chars]" separator = "═" * 46 return f"{separator}\n{header}\n{separator}\n{content}" @staticmethod def _read_file(path: Path) -> List[str]: """Read a memory file and split into entries. No file locking needed: _write_file uses atomic rename, so readers always see either the previous complete file or the new complete file. """ if not path.exists(): return [] try: raw = path.read_text(encoding="utf-8") except (OSError, IOError): return [] if not raw.strip(): return [] # Use ENTRY_DELIMITER for consistency with _write_file. Splitting by "§" # alone would incorrectly split entries that contain "§" in their content. entries = [e.strip() for e in raw.split(ENTRY_DELIMITER)] return [e for e in entries if e] def _detect_external_drift(self, target: str) -> Optional[str]: """Return a backup-path string if on-disk content shows external drift. The memory file is supposed to be a list of small entries the tool wrote, joined by §. Detect drift via two signals: 1. Round-trip mismatch — re-parsing and re-serializing the file doesn't produce identical bytes (rare; would catch oddly-encoded delimiters). 2. Entry-size overflow — any single parsed entry exceeds the store's whole-file char limit. The tool budgets the ENTIRE store against that limit; no single tool-written entry can exceed it. When we see one entry larger than the limit, an external writer (patch tool, shell append, manual edit, sister session) appended free-form content into what the tool will treat as one entry. Flushing would then truncate that entry to the model's new content, discarding the appended bytes — issue #26045. Returns the absolute path of the .bak file when drift was found and backed up; returns None when the file looks tool-shaped. Note: this is an INSTANCE method (not static) because we need the per-target char_limit for signal #2. """ path = self._path_for(target) if not path.exists(): return None try: raw = path.read_text(encoding="utf-8") except (OSError, IOError): return None if not raw.strip(): return None parsed = [e.strip() for e in raw.split(ENTRY_DELIMITER) if e.strip()] roundtrip = ENTRY_DELIMITER.join(parsed) char_limit = self._char_limit(target) max_entry_len = max((len(e) for e in parsed), default=0) drift_detected = (raw.strip() != roundtrip) or (max_entry_len > char_limit) if not drift_detected: return None # Drift confirmed — snapshot the file so the operator can recover # whatever the external writer added, then return the .bak path so # the caller can refuse the mutation. ts = int(time.time()) bak_path = path.with_suffix(path.suffix + f".bak.{ts}") try: bak_path.write_text(raw, encoding="utf-8") except (OSError, IOError): return str(bak_path) + " (BACKUP FAILED — file unchanged on disk)" return str(bak_path) @staticmethod def _write_file(path: Path, entries: List[str]): """Write entries to a memory file using atomic temp-file + rename. Previous implementation used open("w") + flock, but "w" truncates the file *before* the lock is acquired, creating a race window where concurrent readers see an empty file. Atomic rename avoids this: readers always see either the old complete file or the new one. """ content = ENTRY_DELIMITER.join(entries) if entries else "" try: # Write to temp file in same directory (same filesystem for atomic rename) fd, tmp_path = tempfile.mkstemp( dir=str(path.parent), suffix=".tmp", prefix=".mem_" ) try: with os.fdopen(fd, "w", encoding="utf-8") as f: f.write(content) f.flush() os.fsync(f.fileno()) atomic_replace(tmp_path, path) except BaseException: # Clean up temp file on any failure try: os.unlink(tmp_path) except OSError: pass raise except (OSError, IOError) as e: raise RuntimeError(f"Failed to write memory file {path}: {e}") def memory_tool( action: str, target: str = "memory", content: str = None, old_text: str = None, store: Optional[MemoryStore] = None, ) -> str: """ Single entry point for the memory tool. Dispatches to MemoryStore methods. Returns JSON string with results. """ if store is None: return tool_error("Memory is not available. It may be disabled in config or this environment.", success=False) if target not in {"memory", "user"}: return tool_error(f"Invalid target '{target}'. Use 'memory' or 'user'.", success=False) if action == "add": if not content: return tool_error("Content is required for 'add' action.", success=False) result = store.add(target, content) elif action == "replace": if not old_text: return tool_error("old_text is required for 'replace' action.", success=False) if not content: return tool_error("content is required for 'replace' action.", success=False) result = store.replace(target, old_text, content) elif action == "remove": if not old_text: return tool_error("old_text is required for 'remove' action.", success=False) result = store.remove(target, old_text) else: return tool_error(f"Unknown action '{action}'. Use: add, replace, remove", success=False) return json.dumps(result, ensure_ascii=False) def check_memory_requirements() -> bool: """Memory tool has no external requirements -- always available.""" return True # ============================================================================= # OpenAI Function-Calling Schema # ============================================================================= MEMORY_SCHEMA = { "name": "memory", "description": ( "Save durable information to persistent memory that survives across sessions. " "Memory is injected into future turns, so keep it compact and focused on facts " "that will still matter later.\n\n" "WHEN TO SAVE (do this proactively, don't wait to be asked):\n" "- User corrects you or says 'remember this' / 'don't do that again'\n" "- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n" "- You discover something about the environment (OS, installed tools, project structure)\n" "- You learn a convention, API quirk, or workflow specific to this user's setup\n" "- You identify a stable fact that will be useful again in future sessions\n\n" "PRIORITY: User preferences and corrections > environment facts > procedural knowledge. " "The most valuable memory prevents the user from having to repeat themselves.\n\n" "Do NOT save task progress, session outcomes, completed-work logs, or temporary TODO " "state to memory; use session_search to recall those from past transcripts.\n" "If you've discovered a new way to do something, solved a problem that could be " "necessary later, save it as a skill with the skill tool.\n\n" "TWO TARGETS:\n" "- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n" "- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\n" "ACTIONS: add (new entry), replace (update existing -- old_text identifies it), " "remove (delete -- old_text identifies it).\n\n" "SKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state." ), "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": ["add", "replace", "remove"], "description": "The action to perform." }, "target": { "type": "string", "enum": ["memory", "user"], "description": "Which memory store: 'memory' for personal notes, 'user' for user profile." }, "content": { "type": "string", "description": "The entry content. Required for 'add' and 'replace'." }, "old_text": { "type": "string", "description": "Short unique substring identifying the entry to replace or remove." }, }, "required": ["action", "target"], }, } # --- Registry --- from tools.registry import registry, tool_error registry.register( name="memory", toolset="memory", schema=MEMORY_SCHEMA, handler=lambda args, **kw: memory_tool( action=args.get("action", ""), target=args.get("target", "memory"), content=args.get("content"), old_text=args.get("old_text"), store=kw.get("store")), check_fn=check_memory_requirements, emoji="🧠", )