feat: add Honcho AI-native memory integration
Opt-in persistent cross-session user modeling via Honcho. Reads ~/.honcho/config.json as single source of truth (shared with Claude Code, Cursor, and other Honcho-enabled tools). Zero impact when disabled or unconfigured. - honcho_integration/ package (client, session manager, peer resolution) - Host-based config resolution matching claude-honcho/cursor-honcho pattern - Prefetch user context into system prompt per conversation turn - Sync user/assistant messages to Honcho after each exchange - query_user_context tool for mid-conversation dialectic reasoning - Gated activation: requires ~/.honcho/config.json with enabled=true
This commit is contained in:
Erosika
1
cli.py
1
cli.py
@@ -960,6 +960,7 @@ class HermesCLI:
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platform="cli",
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session_db=self._session_db,
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clarify_callback=self._clarify_callback,
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honcho_session_key=self.session_id,
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)
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return True
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except Exception as e:
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@@ -1444,6 +1444,7 @@ class GatewayRunner:
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session_id=session_id,
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tool_progress_callback=progress_callback if tool_progress_enabled else None,
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platform=platform_key,
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honcho_session_key=session_key,
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)
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# Store agent reference for interrupt support
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@@ -127,6 +127,11 @@ DEFAULT_CONFIG = {
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# Never saved to sessions, logs, or trajectories.
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"prefill_messages_file": "",
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# Honcho AI-native memory -- reads ~/.honcho/config.json as single source of truth.
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# This section is only needed for hermes-specific overrides; everything else
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# (apiKey, workspace, peerName, sessions, enabled) comes from the global config.
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"honcho": {},
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# Permanently allowed dangerous command patterns (added via "always" approval)
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"command_allowlist": [],
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@@ -229,6 +234,16 @@ OPTIONAL_ENV_VARS = {
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"category": "tool",
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},
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# ── Honcho ──
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"HONCHO_API_KEY": {
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"description": "Honcho API key for AI-native persistent memory",
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"prompt": "Honcho API key",
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"url": "https://app.honcho.dev",
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"tools": ["query_user_context"],
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"password": True,
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"category": "tool",
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},
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# ── Messaging platforms ──
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"TELEGRAM_BOT_TOKEN": {
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"description": "Telegram bot token from @BotFather",
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@@ -769,7 +784,7 @@ def set_config_value(key: str, value: str):
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'FAL_KEY', 'TELEGRAM_BOT_TOKEN', 'DISCORD_BOT_TOKEN',
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'TERMINAL_SSH_HOST', 'TERMINAL_SSH_USER', 'TERMINAL_SSH_KEY',
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'SUDO_PASSWORD', 'SLACK_BOT_TOKEN', 'SLACK_APP_TOKEN',
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'GITHUB_TOKEN',
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'GITHUB_TOKEN', 'HONCHO_API_KEY',
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]
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if key.upper() in api_keys or key.upper().startswith('TERMINAL_SSH'):
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9
honcho_integration/__init__.py
Normal file
9
honcho_integration/__init__.py
Normal file
@@ -0,0 +1,9 @@
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"""Honcho integration for AI-native memory.
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This package is only active when honcho.enabled=true in config and
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HONCHO_API_KEY is set. All honcho-ai imports are deferred to avoid
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ImportError when the package is not installed.
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Named ``honcho_integration`` (not ``honcho``) to avoid shadowing the
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``honcho`` package installed by the ``honcho-ai`` SDK.
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"""
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191
honcho_integration/client.py
Normal file
191
honcho_integration/client.py
Normal file
@@ -0,0 +1,191 @@
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"""Honcho client initialization and configuration.
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Reads the global ~/.honcho/config.json when available, falling back
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to environment variables.
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Resolution order for host-specific settings:
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1. Explicit host block fields (always win)
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2. Flat/global fields from config root
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3. Defaults (host name as workspace/peer)
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"""
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from __future__ import annotations
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import json
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import os
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import logging
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any, TYPE_CHECKING
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if TYPE_CHECKING:
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from honcho import Honcho
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logger = logging.getLogger(__name__)
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GLOBAL_CONFIG_PATH = Path.home() / ".honcho" / "config.json"
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HOST = "hermes"
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@dataclass
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class HonchoClientConfig:
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"""Configuration for Honcho client, resolved for a specific host."""
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host: str = HOST
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workspace_id: str = "hermes"
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api_key: str | None = None
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environment: str = "production"
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# Identity
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peer_name: str | None = None
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ai_peer: str = "hermes"
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linked_hosts: list[str] = field(default_factory=list)
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# Toggles
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enabled: bool = False
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save_messages: bool = True
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# Session resolution
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session_strategy: str = "per-directory"
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session_peer_prefix: bool = False
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sessions: dict[str, str] = field(default_factory=dict)
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# Raw global config for anything else consumers need
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raw: dict[str, Any] = field(default_factory=dict)
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@classmethod
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def from_env(cls, workspace_id: str = "hermes") -> HonchoClientConfig:
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"""Create config from environment variables (fallback)."""
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return cls(
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workspace_id=workspace_id,
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api_key=os.environ.get("HONCHO_API_KEY"),
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environment=os.environ.get("HONCHO_ENVIRONMENT", "production"),
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enabled=True,
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)
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@classmethod
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def from_global_config(
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cls,
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host: str = HOST,
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config_path: Path | None = None,
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) -> HonchoClientConfig:
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"""Create config from ~/.honcho/config.json.
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Falls back to environment variables if the file doesn't exist.
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"""
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path = config_path or GLOBAL_CONFIG_PATH
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if not path.exists():
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logger.debug("No global Honcho config at %s, falling back to env", path)
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return cls.from_env()
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try:
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raw = json.loads(path.read_text(encoding="utf-8"))
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except (json.JSONDecodeError, OSError) as e:
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logger.warning("Failed to read %s: %s, falling back to env", path, e)
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return cls.from_env()
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host_block = (raw.get("hosts") or {}).get(host, {})
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# Explicit host block fields win, then flat/global, then defaults
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workspace = (
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host_block.get("workspace")
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or raw.get("workspace")
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or host
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)
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ai_peer = (
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host_block.get("aiPeer")
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or raw.get("aiPeer")
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or host
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)
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linked_hosts = host_block.get("linkedHosts", [])
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return cls(
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host=host,
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workspace_id=workspace,
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api_key=raw.get("apiKey") or os.environ.get("HONCHO_API_KEY"),
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environment=raw.get("environment", "production"),
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peer_name=raw.get("peerName"),
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ai_peer=ai_peer,
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linked_hosts=linked_hosts,
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enabled=raw.get("enabled", False),
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save_messages=raw.get("saveMessages", True),
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session_strategy=raw.get("sessionStrategy", "per-directory"),
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session_peer_prefix=raw.get("sessionPeerPrefix", False),
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sessions=raw.get("sessions", {}),
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raw=raw,
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)
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def resolve_session_name(self, cwd: str | None = None) -> str | None:
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"""Resolve session name for a directory.
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Checks manual overrides first, then derives from directory name.
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"""
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if not cwd:
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cwd = os.getcwd()
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# Manual override
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manual = self.sessions.get(cwd)
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if manual:
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return manual
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# Derive from directory basename
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base = Path(cwd).name
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if self.session_peer_prefix and self.peer_name:
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return f"{self.peer_name}-{base}"
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return base
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def get_linked_workspaces(self) -> list[str]:
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"""Resolve linked host keys to workspace names."""
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hosts = self.raw.get("hosts", {})
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workspaces = []
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for host_key in self.linked_hosts:
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block = hosts.get(host_key, {})
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ws = block.get("workspace") or host_key
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if ws != self.workspace_id:
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workspaces.append(ws)
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return workspaces
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_honcho_client: Honcho | None = None
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def get_honcho_client(config: HonchoClientConfig | None = None) -> Honcho:
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"""Get or create the Honcho client singleton.
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When no config is provided, attempts to load ~/.honcho/config.json
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first, falling back to environment variables.
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"""
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global _honcho_client
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if _honcho_client is not None:
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return _honcho_client
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if config is None:
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config = HonchoClientConfig.from_global_config()
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if not config.api_key:
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raise ValueError(
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"Honcho API key not found. Set it in ~/.honcho/config.json "
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"or the HONCHO_API_KEY environment variable. "
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"Get an API key from https://app.honcho.dev"
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)
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try:
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from honcho import Honcho
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except ImportError:
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raise ImportError(
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"honcho-ai is required for Honcho integration. "
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"Install it with: pip install honcho-ai"
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)
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logger.info("Initializing Honcho client (host: %s, workspace: %s)", config.host, config.workspace_id)
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_honcho_client = Honcho(
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workspace_id=config.workspace_id,
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api_key=config.api_key,
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environment=config.environment,
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)
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return _honcho_client
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def reset_honcho_client() -> None:
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"""Reset the Honcho client singleton (useful for testing)."""
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global _honcho_client
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_honcho_client = None
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538
honcho_integration/session.py
Normal file
538
honcho_integration/session.py
Normal file
@@ -0,0 +1,538 @@
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"""Honcho-based session management for conversation history."""
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from __future__ import annotations
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import re
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import logging
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from dataclasses import dataclass, field
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from datetime import datetime
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from typing import Any, TYPE_CHECKING
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from honcho_integration.client import get_honcho_client
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if TYPE_CHECKING:
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from honcho import Honcho
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logger = logging.getLogger(__name__)
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@dataclass
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class HonchoSession:
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"""
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A conversation session backed by Honcho.
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Provides a local message cache that syncs to Honcho's
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AI-native memory system for user modeling.
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"""
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key: str # channel:chat_id
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user_peer_id: str # Honcho peer ID for the user
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assistant_peer_id: str # Honcho peer ID for the assistant
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honcho_session_id: str # Honcho session ID
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messages: list[dict[str, Any]] = field(default_factory=list)
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created_at: datetime = field(default_factory=datetime.now)
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updated_at: datetime = field(default_factory=datetime.now)
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metadata: dict[str, Any] = field(default_factory=dict)
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def add_message(self, role: str, content: str, **kwargs: Any) -> None:
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"""Add a message to the local cache."""
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msg = {
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"role": role,
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"content": content,
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"timestamp": datetime.now().isoformat(),
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**kwargs,
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}
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self.messages.append(msg)
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self.updated_at = datetime.now()
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def get_history(self, max_messages: int = 50) -> list[dict[str, Any]]:
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"""Get message history for LLM context."""
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recent = (
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self.messages[-max_messages:]
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if len(self.messages) > max_messages
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else self.messages
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)
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return [{"role": m["role"], "content": m["content"]} for m in recent]
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def clear(self) -> None:
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"""Clear all messages in the session."""
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self.messages = []
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self.updated_at = datetime.now()
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class HonchoSessionManager:
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"""
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Manages conversation sessions using Honcho.
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Runs alongside hermes' existing SQLite state and file-based memory,
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adding persistent cross-session user modeling via Honcho's AI-native memory.
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"""
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def __init__(
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self,
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honcho: Honcho | None = None,
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context_tokens: int | None = None,
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config: Any | None = None,
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):
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"""
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Initialize the session manager.
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Args:
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honcho: Optional Honcho client. If not provided, uses the singleton.
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context_tokens: Max tokens for context() calls (None = Honcho default).
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config: HonchoClientConfig from global config (provides peer_name, ai_peer, etc.).
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"""
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self._honcho = honcho
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self._context_tokens = context_tokens
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self._config = config
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self._cache: dict[str, HonchoSession] = {}
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self._peers_cache: dict[str, Any] = {}
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self._sessions_cache: dict[str, Any] = {}
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@property
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def honcho(self) -> Honcho:
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"""Get the Honcho client, initializing if needed."""
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if self._honcho is None:
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self._honcho = get_honcho_client()
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return self._honcho
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def _get_or_create_peer(self, peer_id: str) -> Any:
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"""
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Get or create a Honcho peer.
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Peers are lazy -- no API call until first use.
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Observation settings are controlled per-session via SessionPeerConfig.
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"""
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if peer_id in self._peers_cache:
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return self._peers_cache[peer_id]
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peer = self.honcho.peer(peer_id)
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self._peers_cache[peer_id] = peer
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return peer
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def _get_or_create_honcho_session(
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self, session_id: str, user_peer: Any, assistant_peer: Any
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) -> tuple[Any, list]:
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"""
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Get or create a Honcho session with peers configured.
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Returns:
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Tuple of (honcho_session, existing_messages).
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"""
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if session_id in self._sessions_cache:
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logger.debug("Honcho session '%s' retrieved from cache", session_id)
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return self._sessions_cache[session_id], []
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session = self.honcho.session(session_id)
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# Configure peer observation settings
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from honcho.session import SessionPeerConfig
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user_config = SessionPeerConfig(observe_me=True, observe_others=True)
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ai_config = SessionPeerConfig(observe_me=False, observe_others=True)
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session.add_peers([(user_peer, user_config), (assistant_peer, ai_config)])
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# Load existing messages via context() - single call for messages + metadata
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existing_messages = []
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try:
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ctx = session.context(summary=True, tokens=self._context_tokens)
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existing_messages = ctx.messages or []
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# Verify chronological ordering
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if existing_messages and len(existing_messages) > 1:
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timestamps = [m.created_at for m in existing_messages if m.created_at]
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if timestamps and timestamps != sorted(timestamps):
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logger.warning(
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"Honcho messages not chronologically ordered for session '%s', sorting",
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session_id,
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)
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existing_messages = sorted(
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existing_messages,
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key=lambda m: m.created_at or datetime.min,
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)
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if existing_messages:
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logger.info(
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"Honcho session '%s' retrieved (%d existing messages)",
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session_id, len(existing_messages),
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)
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else:
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logger.info("Honcho session '%s' created (new)", session_id)
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except Exception as e:
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logger.warning(
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"Honcho session '%s' loaded (failed to fetch context: %s)",
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session_id, e,
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)
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self._sessions_cache[session_id] = session
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return session, existing_messages
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def _sanitize_id(self, id_str: str) -> str:
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"""Sanitize an ID to match Honcho's pattern: ^[a-zA-Z0-9_-]+"""
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return re.sub(r'[^a-zA-Z0-9_-]', '-', id_str)
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def get_or_create(self, key: str) -> HonchoSession:
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"""
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Get an existing session or create a new one.
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Args:
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key: Session key (usually channel:chat_id).
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Returns:
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The session.
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"""
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if key in self._cache:
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logger.debug("Local session cache hit: %s", key)
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return self._cache[key]
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# Use peer names from global config when available
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if self._config and self._config.peer_name:
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user_peer_id = self._sanitize_id(self._config.peer_name)
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else:
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# Fallback: derive from session key
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parts = key.split(":", 1)
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channel = parts[0] if len(parts) > 1 else "default"
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chat_id = parts[1] if len(parts) > 1 else key
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user_peer_id = self._sanitize_id(f"user-{channel}-{chat_id}")
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assistant_peer_id = (
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self._config.ai_peer if self._config else "hermes-assistant"
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)
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# Sanitize session ID for Honcho
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honcho_session_id = self._sanitize_id(key)
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# Get or create peers
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user_peer = self._get_or_create_peer(user_peer_id)
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assistant_peer = self._get_or_create_peer(assistant_peer_id)
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# Get or create Honcho session
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honcho_session, existing_messages = self._get_or_create_honcho_session(
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honcho_session_id, user_peer, assistant_peer
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)
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# Convert Honcho messages to local format
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local_messages = []
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for msg in existing_messages:
|
||||
role = "assistant" if msg.peer_id == assistant_peer_id else "user"
|
||||
local_messages.append({
|
||||
"role": role,
|
||||
"content": msg.content,
|
||||
"timestamp": msg.created_at.isoformat() if msg.created_at else "",
|
||||
"_synced": True, # Already in Honcho
|
||||
})
|
||||
|
||||
# Create local session wrapper with existing messages
|
||||
session = HonchoSession(
|
||||
key=key,
|
||||
user_peer_id=user_peer_id,
|
||||
assistant_peer_id=assistant_peer_id,
|
||||
honcho_session_id=honcho_session_id,
|
||||
messages=local_messages,
|
||||
)
|
||||
|
||||
self._cache[key] = session
|
||||
return session
|
||||
|
||||
def save(self, session: HonchoSession) -> None:
|
||||
"""
|
||||
Save messages to Honcho.
|
||||
|
||||
Syncs only new (unsynced) messages from the local cache.
|
||||
"""
|
||||
if not session.messages:
|
||||
return
|
||||
|
||||
# Get the Honcho session and peers
|
||||
user_peer = self._get_or_create_peer(session.user_peer_id)
|
||||
assistant_peer = self._get_or_create_peer(session.assistant_peer_id)
|
||||
honcho_session = self._sessions_cache.get(session.honcho_session_id)
|
||||
|
||||
if not honcho_session:
|
||||
honcho_session, _ = self._get_or_create_honcho_session(
|
||||
session.honcho_session_id, user_peer, assistant_peer
|
||||
)
|
||||
|
||||
# Only send new messages (those without a '_synced' flag)
|
||||
new_messages = [m for m in session.messages if not m.get("_synced")]
|
||||
|
||||
if not new_messages:
|
||||
return
|
||||
|
||||
honcho_messages = []
|
||||
for msg in new_messages:
|
||||
peer = user_peer if msg["role"] == "user" else assistant_peer
|
||||
honcho_messages.append(peer.message(msg["content"]))
|
||||
|
||||
try:
|
||||
honcho_session.add_messages(honcho_messages)
|
||||
for msg in new_messages:
|
||||
msg["_synced"] = True
|
||||
logger.debug("Synced %d messages to Honcho for %s", len(honcho_messages), session.key)
|
||||
except Exception as e:
|
||||
for msg in new_messages:
|
||||
msg["_synced"] = False
|
||||
logger.error("Failed to sync messages to Honcho: %s", e)
|
||||
|
||||
# Update cache
|
||||
self._cache[session.key] = session
|
||||
|
||||
def delete(self, key: str) -> bool:
|
||||
"""Delete a session from local cache."""
|
||||
if key in self._cache:
|
||||
del self._cache[key]
|
||||
return True
|
||||
return False
|
||||
|
||||
def new_session(self, key: str) -> HonchoSession:
|
||||
"""
|
||||
Create a new session, preserving the old one for user modeling.
|
||||
|
||||
Creates a fresh session with a new ID while keeping the old
|
||||
session's data in Honcho for continued user modeling.
|
||||
"""
|
||||
import time
|
||||
|
||||
# Remove old session from caches (but don't delete from Honcho)
|
||||
old_session = self._cache.pop(key, None)
|
||||
if old_session:
|
||||
self._sessions_cache.pop(old_session.honcho_session_id, None)
|
||||
|
||||
# Create new session with timestamp suffix
|
||||
timestamp = int(time.time())
|
||||
new_key = f"{key}:{timestamp}"
|
||||
|
||||
# get_or_create will create a fresh session
|
||||
session = self.get_or_create(new_key)
|
||||
|
||||
# Cache under both original key and timestamped key
|
||||
self._cache[key] = session
|
||||
self._cache[new_key] = session
|
||||
|
||||
logger.info("Created new session for %s (honcho: %s)", key, session.honcho_session_id)
|
||||
return session
|
||||
|
||||
def get_user_context(self, session_key: str, query: str) -> str:
|
||||
"""
|
||||
Query Honcho's dialectic chat for user context.
|
||||
|
||||
Args:
|
||||
session_key: The session key to get context for.
|
||||
query: Natural language question about the user.
|
||||
|
||||
Returns:
|
||||
Honcho's response about the user.
|
||||
"""
|
||||
session = self._cache.get(session_key)
|
||||
if not session:
|
||||
return "No session found for this context."
|
||||
|
||||
user_peer = self._get_or_create_peer(session.user_peer_id)
|
||||
|
||||
try:
|
||||
return user_peer.chat(query)
|
||||
except Exception as e:
|
||||
logger.error("Failed to get user context from Honcho: %s", e)
|
||||
return f"Unable to retrieve user context: {e}"
|
||||
|
||||
def get_prefetch_context(self, session_key: str, user_message: str | None = None) -> dict[str, str]:
|
||||
"""
|
||||
Pre-fetch user context using Honcho's context() method.
|
||||
|
||||
Single API call that returns the user's representation
|
||||
and peer card, using semantic search based on the user's message.
|
||||
|
||||
Args:
|
||||
session_key: The session key to get context for.
|
||||
user_message: The user's message for semantic search.
|
||||
|
||||
Returns:
|
||||
Dictionary with 'representation' and 'card' keys.
|
||||
"""
|
||||
session = self._cache.get(session_key)
|
||||
if not session:
|
||||
return {}
|
||||
|
||||
honcho_session = self._sessions_cache.get(session.honcho_session_id)
|
||||
if not honcho_session:
|
||||
return {}
|
||||
|
||||
try:
|
||||
ctx = honcho_session.context(
|
||||
summary=False,
|
||||
tokens=self._context_tokens,
|
||||
peer_target=session.user_peer_id,
|
||||
search_query=user_message,
|
||||
)
|
||||
# peer_card is list[str] in SDK v2, join for prompt injection
|
||||
card = ctx.peer_card or []
|
||||
card_str = "\n".join(card) if isinstance(card, list) else str(card)
|
||||
return {
|
||||
"representation": ctx.peer_representation or "",
|
||||
"card": card_str,
|
||||
}
|
||||
except Exception as e:
|
||||
logger.warning("Failed to fetch context from Honcho: %s", e)
|
||||
return {}
|
||||
|
||||
def migrate_local_history(self, session_key: str, messages: list[dict[str, Any]]) -> bool:
|
||||
"""
|
||||
Upload local session history to Honcho as a file.
|
||||
|
||||
Used when Honcho activates mid-conversation to preserve prior context.
|
||||
|
||||
Args:
|
||||
session_key: The session key (e.g., "telegram:123456").
|
||||
messages: Local messages (dicts with role, content, timestamp).
|
||||
|
||||
Returns:
|
||||
True if upload succeeded, False otherwise.
|
||||
"""
|
||||
sanitized = self._sanitize_id(session_key)
|
||||
honcho_session = self._sessions_cache.get(sanitized)
|
||||
if not honcho_session:
|
||||
logger.warning("No Honcho session cached for '%s', skipping migration", session_key)
|
||||
return False
|
||||
|
||||
# Resolve user peer for attribution
|
||||
parts = session_key.split(":", 1)
|
||||
channel = parts[0] if len(parts) > 1 else "default"
|
||||
chat_id = parts[1] if len(parts) > 1 else session_key
|
||||
user_peer_id = self._sanitize_id(f"user-{channel}-{chat_id}")
|
||||
user_peer = self._peers_cache.get(user_peer_id)
|
||||
if not user_peer:
|
||||
logger.warning("No user peer cached for '%s', skipping migration", user_peer_id)
|
||||
return False
|
||||
|
||||
content_bytes = self._format_migration_transcript(session_key, messages)
|
||||
first_ts = messages[0].get("timestamp") if messages else None
|
||||
|
||||
try:
|
||||
honcho_session.upload_file(
|
||||
file=("prior_history.txt", content_bytes, "text/plain"),
|
||||
peer=user_peer,
|
||||
metadata={"source": "local_jsonl", "count": len(messages)},
|
||||
created_at=first_ts,
|
||||
)
|
||||
logger.info("Migrated %d local messages to Honcho for %s", len(messages), session_key)
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error("Failed to upload local history to Honcho for %s: %s", session_key, e)
|
||||
return False
|
||||
|
||||
@staticmethod
|
||||
def _format_migration_transcript(session_key: str, messages: list[dict[str, Any]]) -> bytes:
|
||||
"""Format local messages as an XML transcript for Honcho file upload."""
|
||||
timestamps = [m.get("timestamp", "") for m in messages]
|
||||
time_range = f"{timestamps[0]} to {timestamps[-1]}" if timestamps else "unknown"
|
||||
|
||||
lines = [
|
||||
"<prior_conversation_history>",
|
||||
"<context>",
|
||||
"This conversation history occurred BEFORE the Honcho memory system was activated.",
|
||||
"These messages are the preceding elements of this conversation session and should",
|
||||
"be treated as foundational context for all subsequent interactions. The user and",
|
||||
"assistant have already established rapport through these exchanges.",
|
||||
"</context>",
|
||||
"",
|
||||
f'<transcript session_key="{session_key}" message_count="{len(messages)}"',
|
||||
f' time_range="{time_range}">',
|
||||
"",
|
||||
]
|
||||
for msg in messages:
|
||||
ts = msg.get("timestamp", "?")
|
||||
role = msg.get("role", "unknown")
|
||||
content = msg.get("content", "")
|
||||
lines.append(f"[{ts}] {role}: {content}")
|
||||
|
||||
lines.append("")
|
||||
lines.append("</transcript>")
|
||||
lines.append("</prior_conversation_history>")
|
||||
|
||||
return "\n".join(lines).encode("utf-8")
|
||||
|
||||
def migrate_memory_files(self, session_key: str, memory_dir: str) -> bool:
|
||||
"""
|
||||
Upload MEMORY.md and USER.md to Honcho as files.
|
||||
|
||||
Used when Honcho activates on an instance that already has locally
|
||||
consolidated memory. Backwards compatible -- skips if files don't exist.
|
||||
|
||||
Args:
|
||||
session_key: The session key to associate files with.
|
||||
memory_dir: Path to the memories directory (~/.hermes/memories/).
|
||||
|
||||
Returns:
|
||||
True if at least one file was uploaded, False otherwise.
|
||||
"""
|
||||
from pathlib import Path
|
||||
memory_path = Path(memory_dir)
|
||||
|
||||
if not memory_path.exists():
|
||||
return False
|
||||
|
||||
sanitized = self._sanitize_id(session_key)
|
||||
honcho_session = self._sessions_cache.get(sanitized)
|
||||
if not honcho_session:
|
||||
logger.warning("No Honcho session cached for '%s', skipping memory migration", session_key)
|
||||
return False
|
||||
|
||||
# Resolve user peer for attribution
|
||||
parts = session_key.split(":", 1)
|
||||
channel = parts[0] if len(parts) > 1 else "default"
|
||||
chat_id = parts[1] if len(parts) > 1 else session_key
|
||||
user_peer_id = self._sanitize_id(f"user-{channel}-{chat_id}")
|
||||
user_peer = self._peers_cache.get(user_peer_id)
|
||||
if not user_peer:
|
||||
logger.warning("No user peer cached for '%s', skipping memory migration", user_peer_id)
|
||||
return False
|
||||
|
||||
uploaded = False
|
||||
files = [
|
||||
("MEMORY.md", "consolidated_memory.md", "Long-term agent notes and preferences"),
|
||||
("USER.md", "user_profile.md", "User profile and preferences"),
|
||||
]
|
||||
|
||||
for filename, upload_name, description in files:
|
||||
filepath = memory_path / filename
|
||||
if not filepath.exists():
|
||||
continue
|
||||
content = filepath.read_text(encoding="utf-8").strip()
|
||||
if not content:
|
||||
continue
|
||||
|
||||
wrapped = (
|
||||
f"<prior_memory_file>\n"
|
||||
f"<context>\n"
|
||||
f"This file was consolidated from local conversations BEFORE Honcho was activated.\n"
|
||||
f"{description}. Treat as foundational context for this user.\n"
|
||||
f"</context>\n"
|
||||
f"\n"
|
||||
f"{content}\n"
|
||||
f"</prior_memory_file>\n"
|
||||
)
|
||||
|
||||
try:
|
||||
honcho_session.upload_file(
|
||||
file=(upload_name, wrapped.encode("utf-8"), "text/plain"),
|
||||
peer=user_peer,
|
||||
metadata={"source": "local_memory", "original_file": filename},
|
||||
)
|
||||
logger.info("Uploaded %s to Honcho for %s", filename, session_key)
|
||||
uploaded = True
|
||||
except Exception as e:
|
||||
logger.error("Failed to upload %s to Honcho: %s", filename, e)
|
||||
|
||||
return uploaded
|
||||
|
||||
def list_sessions(self) -> list[dict[str, Any]]:
|
||||
"""List all cached sessions."""
|
||||
return [
|
||||
{
|
||||
"key": s.key,
|
||||
"created_at": s.created_at.isoformat(),
|
||||
"updated_at": s.updated_at.isoformat(),
|
||||
"message_count": len(s.messages),
|
||||
}
|
||||
for s in self._cache.values()
|
||||
]
|
||||
@@ -93,6 +93,7 @@ def _discover_tools():
|
||||
"tools.delegate_tool",
|
||||
"tools.process_registry",
|
||||
"tools.send_message_tool",
|
||||
"tools.honcho_tools",
|
||||
]
|
||||
import importlib
|
||||
for mod_name in _modules:
|
||||
|
||||
@@ -46,6 +46,7 @@ slack = ["slack-bolt>=1.18.0", "slack-sdk>=3.27.0"]
|
||||
cli = ["simple-term-menu"]
|
||||
tts-premium = ["elevenlabs"]
|
||||
pty = ["ptyprocess>=0.7.0"]
|
||||
honcho = ["honcho-ai>=2.0.1"]
|
||||
all = [
|
||||
"hermes-agent[modal]",
|
||||
"hermes-agent[messaging]",
|
||||
@@ -55,6 +56,7 @@ all = [
|
||||
"hermes-agent[tts-premium]",
|
||||
"hermes-agent[slack]",
|
||||
"hermes-agent[pty]",
|
||||
"hermes-agent[honcho]",
|
||||
]
|
||||
|
||||
[project.scripts]
|
||||
@@ -65,7 +67,7 @@ hermes-agent = "run_agent:main"
|
||||
py-modules = ["run_agent", "model_tools", "toolsets", "batch_runner", "trajectory_compressor", "toolset_distributions", "cli", "hermes_constants"]
|
||||
|
||||
[tool.setuptools.packages.find]
|
||||
include = ["tools", "hermes_cli", "gateway", "cron"]
|
||||
include = ["tools", "hermes_cli", "gateway", "cron", "honcho_integration"]
|
||||
|
||||
[tool.pytest.ini_options]
|
||||
testpaths = ["tests"]
|
||||
|
||||
99
run_agent.py
99
run_agent.py
@@ -131,6 +131,7 @@ class AIAgent:
|
||||
skip_context_files: bool = False,
|
||||
skip_memory: bool = False,
|
||||
session_db=None,
|
||||
honcho_session_key: str = None,
|
||||
):
|
||||
"""
|
||||
Initialize the AI Agent.
|
||||
@@ -168,6 +169,8 @@ class AIAgent:
|
||||
skip_context_files (bool): If True, skip auto-injection of SOUL.md, AGENTS.md, and .cursorrules
|
||||
into the system prompt. Use this for batch processing and data generation to avoid
|
||||
polluting trajectories with user-specific persona or project instructions.
|
||||
honcho_session_key (str): Session key for Honcho integration (e.g., "telegram:123456" or CLI session_id).
|
||||
When provided and Honcho is enabled in config, enables persistent cross-session user modeling.
|
||||
"""
|
||||
self.model = model
|
||||
self.max_iterations = max_iterations
|
||||
@@ -418,6 +421,45 @@ class AIAgent:
|
||||
except Exception:
|
||||
pass # Memory is optional -- don't break agent init
|
||||
|
||||
# Honcho AI-native memory (cross-session user modeling)
|
||||
# Reads ~/.honcho/config.json as the single source of truth.
|
||||
self._honcho = None # HonchoSessionManager | None
|
||||
self._honcho_session_key = honcho_session_key
|
||||
if not skip_memory:
|
||||
try:
|
||||
from honcho_integration.client import HonchoClientConfig, get_honcho_client
|
||||
hcfg = HonchoClientConfig.from_global_config()
|
||||
if hcfg.enabled and hcfg.api_key:
|
||||
from honcho_integration.session import HonchoSessionManager
|
||||
client = get_honcho_client(hcfg)
|
||||
self._honcho = HonchoSessionManager(
|
||||
honcho=client,
|
||||
config=hcfg,
|
||||
)
|
||||
# Resolve session key: explicit arg > global sessions map > fallback
|
||||
if not self._honcho_session_key:
|
||||
self._honcho_session_key = (
|
||||
hcfg.resolve_session_name()
|
||||
or "hermes-default"
|
||||
)
|
||||
# Ensure session exists in Honcho
|
||||
self._honcho.get_or_create(self._honcho_session_key)
|
||||
# Inject session context into the honcho tool module
|
||||
from tools.honcho_tools import set_session_context
|
||||
set_session_context(self._honcho, self._honcho_session_key)
|
||||
logger.info(
|
||||
"Honcho active (session: %s, user: %s, workspace: %s)",
|
||||
self._honcho_session_key, hcfg.peer_name, hcfg.workspace_id,
|
||||
)
|
||||
else:
|
||||
if not hcfg.enabled:
|
||||
logger.debug("Honcho disabled in global config")
|
||||
elif not hcfg.api_key:
|
||||
logger.debug("Honcho enabled but no API key configured")
|
||||
except Exception as e:
|
||||
logger.debug("Honcho init failed (non-fatal): %s", e)
|
||||
self._honcho = None
|
||||
|
||||
# Skills config: nudge interval for skill creation reminders
|
||||
self._skill_nudge_interval = 15
|
||||
try:
|
||||
@@ -1057,6 +1099,45 @@ class AIAgent:
|
||||
"""Check if an interrupt has been requested."""
|
||||
return self._interrupt_requested
|
||||
|
||||
# ── Honcho integration helpers ──
|
||||
|
||||
def _honcho_prefetch(self, user_message: str) -> str:
|
||||
"""Fetch user context from Honcho for system prompt injection.
|
||||
|
||||
Returns a formatted context block, or empty string if unavailable.
|
||||
"""
|
||||
if not self._honcho or not self._honcho_session_key:
|
||||
return ""
|
||||
try:
|
||||
ctx = self._honcho.get_prefetch_context(self._honcho_session_key, user_message)
|
||||
if not ctx:
|
||||
return ""
|
||||
parts = []
|
||||
rep = ctx.get("representation", "")
|
||||
card = ctx.get("card", "")
|
||||
if rep:
|
||||
parts.append(rep)
|
||||
if card:
|
||||
parts.append(card)
|
||||
if not parts:
|
||||
return ""
|
||||
return "# Honcho User Context\n" + "\n\n".join(parts)
|
||||
except Exception as e:
|
||||
logger.debug("Honcho prefetch failed (non-fatal): %s", e)
|
||||
return ""
|
||||
|
||||
def _honcho_sync(self, user_content: str, assistant_content: str) -> None:
|
||||
"""Sync the user/assistant message pair to Honcho."""
|
||||
if not self._honcho or not self._honcho_session_key:
|
||||
return
|
||||
try:
|
||||
session = self._honcho.get_or_create(self._honcho_session_key)
|
||||
session.add_message("user", user_content)
|
||||
session.add_message("assistant", assistant_content)
|
||||
self._honcho.save(session)
|
||||
except Exception as e:
|
||||
logger.debug("Honcho sync failed (non-fatal): %s", e)
|
||||
|
||||
def _build_system_prompt(self, system_message: str = None) -> str:
|
||||
"""
|
||||
Assemble the full system prompt from all layers.
|
||||
@@ -1711,6 +1792,10 @@ class AIAgent:
|
||||
# Track user turns for memory flush and periodic nudge logic
|
||||
self._user_turn_count += 1
|
||||
|
||||
# Preserve the original user message before nudge injection.
|
||||
# Honcho should receive the actual user input, not system nudges.
|
||||
original_user_message = user_message
|
||||
|
||||
# Periodic memory nudge: remind the model to consider saving memories.
|
||||
# Counter resets whenever the memory tool is actually used.
|
||||
if (self._memory_nudge_interval > 0
|
||||
@@ -1735,6 +1820,14 @@ class AIAgent:
|
||||
)
|
||||
self._iters_since_skill = 0
|
||||
|
||||
# Honcho prefetch: retrieve user context for system prompt injection
|
||||
self._honcho_context = ""
|
||||
if self._honcho and self._honcho_session_key:
|
||||
try:
|
||||
self._honcho_context = self._honcho_prefetch(user_message)
|
||||
except Exception as e:
|
||||
logger.debug("Honcho prefetch failed (non-fatal): %s", e)
|
||||
|
||||
# Add user message
|
||||
user_msg = {"role": "user", "content": user_message}
|
||||
messages.append(user_msg)
|
||||
@@ -1813,6 +1906,8 @@ class AIAgent:
|
||||
effective_system = active_system_prompt or ""
|
||||
if self.ephemeral_system_prompt:
|
||||
effective_system = (effective_system + "\n\n" + self.ephemeral_system_prompt).strip()
|
||||
if self._honcho_context:
|
||||
effective_system = (effective_system + "\n\n" + self._honcho_context).strip()
|
||||
if effective_system:
|
||||
api_messages = [{"role": "system", "content": effective_system}] + api_messages
|
||||
|
||||
@@ -2472,6 +2567,10 @@ class AIAgent:
|
||||
# Persist session to both JSON log and SQLite
|
||||
self._persist_session(messages, conversation_history)
|
||||
|
||||
# Sync conversation to Honcho for user modeling
|
||||
if final_response and not interrupted:
|
||||
self._honcho_sync(original_user_message, final_response)
|
||||
|
||||
# Build result with interrupt info if applicable
|
||||
result = {
|
||||
"final_response": final_response,
|
||||
|
||||
102
tools/honcho_tools.py
Normal file
102
tools/honcho_tools.py
Normal file
@@ -0,0 +1,102 @@
|
||||
"""Honcho tool for querying user context via dialectic reasoning.
|
||||
|
||||
Registers ``query_user_context`` -- an LLM-callable tool that asks Honcho
|
||||
about the current user's history, preferences, goals, and communication
|
||||
style. The session key is injected at runtime by the agent loop via
|
||||
``set_session_context()``.
|
||||
"""
|
||||
|
||||
import json
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# ── Module-level state (injected by AIAgent at init time) ──
|
||||
|
||||
_session_manager = None # HonchoSessionManager instance
|
||||
_session_key: str | None = None # Current session key (e.g., "telegram:123456")
|
||||
|
||||
|
||||
def set_session_context(session_manager, session_key: str) -> None:
|
||||
"""Register the active Honcho session manager and key.
|
||||
|
||||
Called by AIAgent.__init__ when Honcho is enabled.
|
||||
"""
|
||||
global _session_manager, _session_key
|
||||
_session_manager = session_manager
|
||||
_session_key = session_key
|
||||
|
||||
|
||||
def clear_session_context() -> None:
|
||||
"""Clear session context (for testing or shutdown)."""
|
||||
global _session_manager, _session_key
|
||||
_session_manager = None
|
||||
_session_key = None
|
||||
|
||||
|
||||
# ── Tool schema ──
|
||||
|
||||
HONCHO_TOOL_SCHEMA = {
|
||||
"name": "query_user_context",
|
||||
"description": (
|
||||
"Query Honcho to retrieve relevant context about the user based on their "
|
||||
"history and preferences. Use this when you need to understand the user's "
|
||||
"background, preferences, past interactions, or goals. This helps you "
|
||||
"personalize your responses and provide more relevant assistance."
|
||||
),
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"query": {
|
||||
"type": "string",
|
||||
"description": (
|
||||
"A natural language question about the user. Examples: "
|
||||
"'What are this user's main goals?', "
|
||||
"'What communication style does this user prefer?', "
|
||||
"'What topics has this user discussed recently?', "
|
||||
"'What is this user's technical expertise level?'"
|
||||
),
|
||||
}
|
||||
},
|
||||
"required": ["query"],
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
# ── Tool handler ──
|
||||
|
||||
def _handle_query_user_context(args: dict, **kw) -> str:
|
||||
"""Execute the Honcho context query."""
|
||||
query = args.get("query", "")
|
||||
if not query:
|
||||
return json.dumps({"error": "Missing required parameter: query"})
|
||||
|
||||
if not _session_manager or not _session_key:
|
||||
return json.dumps({"error": "Honcho is not active for this session."})
|
||||
|
||||
try:
|
||||
result = _session_manager.get_user_context(_session_key, query)
|
||||
return json.dumps({"result": result})
|
||||
except Exception as e:
|
||||
logger.error("Error querying Honcho user context: %s", e)
|
||||
return json.dumps({"error": f"Failed to query user context: {e}"})
|
||||
|
||||
|
||||
# ── Availability check ──
|
||||
|
||||
def _check_honcho_available() -> bool:
|
||||
"""Tool is only available when Honcho is active."""
|
||||
return _session_manager is not None and _session_key is not None
|
||||
|
||||
|
||||
# ── Registration ──
|
||||
|
||||
from tools.registry import registry
|
||||
|
||||
registry.register(
|
||||
name="query_user_context",
|
||||
toolset="honcho",
|
||||
schema=HONCHO_TOOL_SCHEMA,
|
||||
handler=_handle_query_user_context,
|
||||
check_fn=_check_honcho_available,
|
||||
)
|
||||
@@ -60,6 +60,8 @@ _HERMES_CORE_TOOLS = [
|
||||
"schedule_cronjob", "list_cronjobs", "remove_cronjob",
|
||||
# Cross-platform messaging (gated on gateway running via check_fn)
|
||||
"send_message",
|
||||
# Honcho user context (gated on honcho being active via check_fn)
|
||||
"query_user_context",
|
||||
]
|
||||
|
||||
|
||||
@@ -186,6 +188,12 @@ TOOLSETS = {
|
||||
"includes": []
|
||||
},
|
||||
|
||||
"honcho": {
|
||||
"description": "Honcho AI-native memory for persistent cross-session user modeling",
|
||||
"tools": ["query_user_context"],
|
||||
"includes": []
|
||||
},
|
||||
|
||||
|
||||
# Scenario-specific toolsets
|
||||
|
||||
|
||||
Reference in New Issue
Block a user