Files
hermes-agent/agent/memory_provider.py
Teknium f503eb6647 feat(memory): add pluggable memory provider interface with profile isolation
Introduces a pluggable MemoryProvider ABC so external memory backends can
integrate with Hermes without modifying core files. Each backend becomes a
plugin implementing a standard interface, orchestrated by MemoryManager.

Key architecture:
- agent/memory_provider.py — ABC with core + optional lifecycle hooks
- agent/memory_manager.py — single integration point in the agent loop
- agent/builtin_memory_provider.py — wraps existing MEMORY.md/USER.md

Profile isolation fixes applied to all 6 shipped plugins:
- Cognitive Memory: use get_hermes_home() instead of raw env var
- Hindsight Memory: check $HERMES_HOME/hindsight/config.json first,
  fall back to legacy ~/.hindsight/ for backward compat
- Hermes Memory Store: replace hardcoded ~/.hermes paths with
  get_hermes_home() for config loading and DB path defaults
- Mem0 Memory: use get_hermes_home() instead of raw env var
- RetainDB Memory: auto-derive profile-scoped project name from
  hermes_home path (hermes-<profile>), explicit env var overrides
- OpenViking Memory: read-only, no local state, isolation via .env

MemoryManager.initialize_all() now injects hermes_home into kwargs so
every provider can resolve profile-scoped storage without importing
get_hermes_home() themselves.

Plugin system: adds register_memory_provider() to PluginContext and
get_plugin_memory_providers() accessor.

Based on PR #3825. 46 tests (37 unit + 5 E2E + 4 plugin registration).
2026-03-30 17:09:11 -07:00

176 lines
6.8 KiB
Python

"""Abstract base class for pluggable memory providers.
Memory providers give the agent persistent recall across sessions. Multiple
providers can be active simultaneously — the MemoryManager orchestrates them.
Built-in memory (MEMORY.md / USER.md) is always active as the first provider.
External providers (Honcho, Hindsight, Mem0, etc.) are additive — they never
disable the built-in store.
Three registration paths:
1. Built-in: BuiltinMemoryProvider — always present, not removable.
2. First-party: Ship with the repo, activated by config (e.g. Honcho).
3. Plugin: External packages register via ctx.register_memory_provider().
Lifecycle (called by MemoryManager, wired in run_agent.py):
initialize() — connect, create resources, warm up
system_prompt_block() — static text for the system prompt
prefetch(query) — background recall before each turn
sync_turn(user, asst) — async write after each turn
get_tool_schemas() — tool schemas to expose to the model
handle_tool_call() — dispatch a tool call
shutdown() — clean exit
Optional hooks (override to opt in):
on_turn_start(turn, message) — per-turn tick (scope cooling, etc.)
on_session_end(messages) — end-of-session extraction
on_pre_compress(messages) — extract before context compression
on_memory_write(action, target, content) — mirror built-in memory writes
"""
from __future__ import annotations
import logging
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional
logger = logging.getLogger(__name__)
class MemoryProvider(ABC):
"""Abstract base class for memory providers."""
@property
@abstractmethod
def name(self) -> str:
"""Short identifier for this provider (e.g. 'builtin', 'honcho', 'hindsight')."""
# -- Core lifecycle (implement these) ------------------------------------
@abstractmethod
def is_available(self) -> bool:
"""Return True if this provider is configured, has credentials, and is ready.
Called during agent init to decide whether to activate the provider.
Should not make network calls — just check config and installed deps.
"""
@abstractmethod
def initialize(self, session_id: str, **kwargs) -> None:
"""Initialize for a session.
Called once at agent startup. May create resources (banks, tables),
establish connections, start background threads, etc.
kwargs always include:
- hermes_home (str): The active HERMES_HOME directory path. Use this
for profile-scoped storage instead of hardcoding ``~/.hermes``.
kwargs may also include: platform, model, user_id, and other session context.
"""
def system_prompt_block(self) -> str:
"""Return text to include in the system prompt.
Called during system prompt assembly. Return empty string to skip.
This is for STATIC provider info (instructions, status). Prefetched
recall context is injected separately via prefetch().
"""
return ""
def prefetch(self, query: str) -> str:
"""Recall relevant context for the upcoming turn.
Called before each API call. Return formatted text to inject as
context, or empty string if nothing relevant. Implementations
should be fast — use background threads for the actual recall
and return cached results here.
"""
return ""
def queue_prefetch(self, query: str) -> None:
"""Queue a background recall for the NEXT turn.
Called after each turn completes. The result will be consumed
by prefetch() on the next turn. Default is no-op — providers
that do background prefetching should override this.
"""
def sync_turn(self, user_content: str, assistant_content: str) -> None:
"""Persist a completed turn to the backend.
Called after each turn. Should be non-blocking — queue for
background processing if the backend has latency.
"""
@abstractmethod
def get_tool_schemas(self) -> List[Dict[str, Any]]:
"""Return tool schemas this provider exposes.
Each schema follows the OpenAI function calling format:
{"name": "...", "description": "...", "parameters": {...}}
Return empty list if this provider has no tools (context-only).
"""
def handle_tool_call(self, tool_name: str, args: Dict[str, Any], **kwargs) -> str:
"""Handle a tool call for one of this provider's tools.
Must return a JSON string (the tool result).
Only called for tool names returned by get_tool_schemas().
"""
raise NotImplementedError(f"Provider {self.name} does not handle tool {tool_name}")
def shutdown(self) -> None:
"""Clean shutdown — flush queues, close connections."""
# -- Optional hooks (override to opt in) ---------------------------------
def on_turn_start(self, turn_number: int, message: str) -> None:
"""Called at the start of each turn with the user message.
Use for turn-counting, scope management, periodic maintenance.
"""
def on_session_end(self, messages: List[Dict[str, Any]]) -> None:
"""Called when a session ends (explicit exit or timeout).
Use for end-of-session fact extraction, summarization, etc.
messages is the full conversation history.
"""
def on_pre_compress(self, messages: List[Dict[str, Any]]) -> None:
"""Called before context compression discards old messages.
Use to extract insights from messages about to be compressed.
messages is the list that will be summarized/discarded.
"""
def get_config_schema(self) -> List[Dict[str, Any]]:
"""Return config fields this provider needs for setup.
Used by 'hermes memory setup' to walk the user through configuration.
Each field is a dict with:
key: config key name (e.g. 'api_key', 'mode')
description: human-readable description
secret: True if this should go to .env (default: False)
required: True if required (default: False)
default: default value (optional)
choices: list of valid values (optional)
url: URL where user can get this credential (optional)
env_var: explicit env var name for secrets (default: auto-generated)
Return empty list if no config needed (e.g. local-only providers).
"""
return []
def on_memory_write(self, action: str, target: str, content: str) -> None:
"""Called when the built-in memory tool writes an entry.
action: 'add', 'replace', or 'remove'
target: 'memory' or 'user'
content: the entry content
Use to mirror built-in memory writes to your backend.
"""