Merge remote-tracking branch 'origin/main' into feat/honcho-async-memory
Made-with: Cursor # Conflicts: # cli.py # tests/test_run_agent.py
This commit is contained in:
Erosika
commit
a0b0dbe6b2
138 changed files with 17829 additions and 1109 deletions
401
gateway/run.py
401
gateway/run.py
|
|
@ -187,6 +187,30 @@ def _resolve_runtime_agent_kwargs() -> dict:
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}
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def _resolve_gateway_model() -> str:
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"""Read model from env/config — mirrors the resolution in _run_agent_sync.
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Without this, temporary AIAgent instances (memory flush, /compress) fall
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back to the hardcoded default ("anthropic/claude-opus-4.6") which fails
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when the active provider is openai-codex.
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"""
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model = os.getenv("HERMES_MODEL") or os.getenv("LLM_MODEL") or "anthropic/claude-opus-4.6"
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try:
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import yaml as _y
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_cfg_path = _hermes_home / "config.yaml"
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if _cfg_path.exists():
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with open(_cfg_path, encoding="utf-8") as _f:
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_cfg = _y.safe_load(_f) or {}
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_model_cfg = _cfg.get("model", {})
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if isinstance(_model_cfg, str):
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model = _model_cfg
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elif isinstance(_model_cfg, dict):
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model = _model_cfg.get("default", model)
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except Exception:
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pass
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return model
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class GatewayRunner:
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"""
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Main gateway controller.
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@ -321,8 +345,14 @@ class GatewayRunner:
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if not runtime_kwargs.get("api_key"):
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return
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# Resolve model from config — AIAgent's default is OpenRouter-
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# formatted ("anthropic/claude-opus-4.6") which fails when the
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# active provider is openai-codex.
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model = _resolve_gateway_model()
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tmp_agent = AIAgent(
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**runtime_kwargs,
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model=model,
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max_iterations=8,
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quiet_mode=True,
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enabled_toolsets=["memory", "skills"],
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@ -743,6 +773,13 @@ class GatewayRunner:
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return None
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return HomeAssistantAdapter(config)
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elif platform == Platform.EMAIL:
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from gateway.platforms.email import EmailAdapter, check_email_requirements
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if not check_email_requirements():
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logger.warning("Email: EMAIL_ADDRESS, EMAIL_PASSWORD, EMAIL_IMAP_HOST, or EMAIL_SMTP_HOST not set")
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return None
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return EmailAdapter(config)
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return None
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def _is_user_authorized(self, source: SessionSource) -> bool:
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@ -772,6 +809,7 @@ class GatewayRunner:
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Platform.WHATSAPP: "WHATSAPP_ALLOWED_USERS",
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Platform.SLACK: "SLACK_ALLOWED_USERS",
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Platform.SIGNAL: "SIGNAL_ALLOWED_USERS",
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Platform.EMAIL: "EMAIL_ALLOWED_USERS",
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}
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platform_allow_all_map = {
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Platform.TELEGRAM: "TELEGRAM_ALLOW_ALL_USERS",
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@ -779,6 +817,7 @@ class GatewayRunner:
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Platform.WHATSAPP: "WHATSAPP_ALLOW_ALL_USERS",
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Platform.SLACK: "SLACK_ALLOW_ALL_USERS",
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Platform.SIGNAL: "SIGNAL_ALLOW_ALL_USERS",
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Platform.EMAIL: "EMAIL_ALLOW_ALL_USERS",
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}
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# Per-platform allow-all flag (e.g., DISCORD_ALLOW_ALL_USERS=true)
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@ -877,7 +916,8 @@ class GatewayRunner:
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_known_commands = {"new", "reset", "help", "status", "stop", "model",
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"personality", "retry", "undo", "sethome", "set-home",
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"compress", "usage", "insights", "reload-mcp", "reload_mcp",
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"update", "title", "resume", "provider", "rollback"}
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"update", "title", "resume", "provider", "rollback",
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"background"}
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if command and command in _known_commands:
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await self.hooks.emit(f"command:{command}", {
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"platform": source.platform.value if source.platform else "",
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@ -939,7 +979,36 @@ class GatewayRunner:
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if command == "rollback":
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return await self._handle_rollback_command(event)
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if command == "background":
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return await self._handle_background_command(event)
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# User-defined quick commands (bypass agent loop, no LLM call)
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if command:
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quick_commands = self.config.get("quick_commands", {})
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if command in quick_commands:
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qcmd = quick_commands[command]
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if qcmd.get("type") == "exec":
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exec_cmd = qcmd.get("command", "")
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if exec_cmd:
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try:
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proc = await asyncio.create_subprocess_shell(
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exec_cmd,
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stdout=asyncio.subprocess.PIPE,
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stderr=asyncio.subprocess.PIPE,
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)
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stdout, stderr = await asyncio.wait_for(proc.communicate(), timeout=30)
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output = (stdout or stderr).decode().strip()
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return output if output else "Command returned no output."
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except asyncio.TimeoutError:
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return "Quick command timed out (30s)."
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except Exception as e:
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return f"Quick command error: {e}"
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else:
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return f"Quick command '/{command}' has no command defined."
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else:
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return f"Quick command '/{command}' has unsupported type (only 'exec' is supported)."
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# Skill slash commands: /skill-name loads the skill and sends to agent
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if command:
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try:
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@ -1021,9 +1090,12 @@ class GatewayRunner:
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# repeated truncation/context failures. Detect this early and
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# compress proactively — before the agent even starts. (#628)
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#
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# Thresholds are derived from the SAME compression config the
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# agent uses (compression.threshold × model context length) so
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# CLI and messaging platforms behave identically.
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# Token source priority:
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# 1. Actual API-reported prompt_tokens from the last turn
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# (stored in session_entry.last_prompt_tokens)
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# 2. Rough char-based estimate (str(msg)//4) with a 1.4x
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# safety factor to account for overestimation on tool-heavy
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# conversations (code/JSON tokenizes at 5-7+ chars/token).
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# -----------------------------------------------------------------
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if history and len(history) >= 4:
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from agent.model_metadata import (
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@ -1074,31 +1146,48 @@ class GatewayRunner:
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_compress_token_threshold = int(
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_hyg_context_length * _hyg_threshold_pct
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)
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# Warn if still huge after compression (95% of context)
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_warn_token_threshold = int(_hyg_context_length * 0.95)
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_msg_count = len(history)
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_approx_tokens = estimate_messages_tokens_rough(history)
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# Prefer actual API-reported tokens from the last turn
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# (stored in session entry) over the rough char-based estimate.
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# The rough estimate (str(msg)//4) overestimates by 30-50% on
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# tool-heavy/code-heavy conversations, causing premature compression.
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_stored_tokens = session_entry.last_prompt_tokens
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if _stored_tokens > 0:
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_approx_tokens = _stored_tokens
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_token_source = "actual"
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else:
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_approx_tokens = estimate_messages_tokens_rough(history)
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# Apply safety factor only for rough estimates
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_compress_token_threshold = int(
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_compress_token_threshold * 1.4
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)
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_warn_token_threshold = int(_warn_token_threshold * 1.4)
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_token_source = "estimated"
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_needs_compress = _approx_tokens >= _compress_token_threshold
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if _needs_compress:
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logger.info(
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"Session hygiene: %s messages, ~%s tokens — auto-compressing "
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"Session hygiene: %s messages, ~%s tokens (%s) — auto-compressing "
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"(threshold: %s%% of %s = %s tokens)",
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_msg_count, f"{_approx_tokens:,}",
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_msg_count, f"{_approx_tokens:,}", _token_source,
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int(_hyg_threshold_pct * 100),
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f"{_hyg_context_length:,}",
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f"{_compress_token_threshold:,}",
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)
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_hyg_adapter = self.adapters.get(source.platform)
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_hyg_meta = {"thread_id": source.thread_id} if source.thread_id else None
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if _hyg_adapter:
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try:
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await _hyg_adapter.send(
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source.chat_id,
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f"🗜️ Session is large ({_msg_count} messages, "
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f"~{_approx_tokens:,} tokens). Auto-compressing..."
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f"~{_approx_tokens:,} tokens). Auto-compressing...",
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metadata=_hyg_meta,
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)
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except Exception:
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pass
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@ -1118,6 +1207,7 @@ class GatewayRunner:
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if len(_hyg_msgs) >= 4:
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_hyg_agent = AIAgent(
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**_hyg_runtime,
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model=_hyg_model,
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max_iterations=4,
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quiet_mode=True,
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enabled_toolsets=["memory"],
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@ -1136,6 +1226,8 @@ class GatewayRunner:
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self.session_store.rewrite_transcript(
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session_entry.session_id, _compressed
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)
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# Reset stored token count — transcript was rewritten
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session_entry.last_prompt_tokens = 0
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history = _compressed
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_new_count = len(_compressed)
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_new_tokens = estimate_messages_tokens_rough(
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@ -1156,7 +1248,8 @@ class GatewayRunner:
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f"🗜️ Compressed: {_msg_count} → "
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f"{_new_count} messages, "
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f"~{_approx_tokens:,} → "
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f"~{_new_tokens:,} tokens"
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f"~{_new_tokens:,} tokens",
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metadata=_hyg_meta,
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)
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except Exception:
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pass
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@ -1176,7 +1269,8 @@ class GatewayRunner:
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"after compression "
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f"(~{_new_tokens:,} tokens). "
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"Consider using /reset to start "
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"fresh if you experience issues."
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"fresh if you experience issues.",
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metadata=_hyg_meta,
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)
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except Exception:
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pass
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@ -1188,6 +1282,7 @@ class GatewayRunner:
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# Compression failed and session is dangerously large
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if _approx_tokens >= _warn_token_threshold:
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_hyg_adapter = self.adapters.get(source.platform)
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_hyg_meta = {"thread_id": source.thread_id} if source.thread_id else None
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if _hyg_adapter:
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try:
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await _hyg_adapter.send(
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|
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@ -1197,7 +1292,8 @@ class GatewayRunner:
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f"~{_approx_tokens:,} tokens) and "
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"auto-compression failed. Consider "
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"using /compress or /reset to avoid "
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"issues."
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"issues.",
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metadata=_hyg_meta,
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)
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except Exception:
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pass
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|
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@ -1393,6 +1489,11 @@ class GatewayRunner:
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{"role": "assistant", "content": response, "timestamp": ts}
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)
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else:
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# The agent already persisted these messages to SQLite via
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# _flush_messages_to_session_db(), so skip the DB write here
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# to prevent the duplicate-write bug (#860). We still write
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# to JSONL for backward compatibility and as a backup.
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agent_persisted = self._session_db is not None
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for msg in new_messages:
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# Skip system messages (they're rebuilt each run)
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if msg.get("role") == "system":
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|
|
@ -1400,11 +1501,15 @@ class GatewayRunner:
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# Add timestamp to each message for debugging
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entry = {**msg, "timestamp": ts}
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self.session_store.append_to_transcript(
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session_entry.session_id, entry
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session_entry.session_id, entry,
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skip_db=agent_persisted,
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)
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|
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# Update session
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self.session_store.update_session(session_entry.session_key)
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# Update session with actual prompt token count from the agent
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self.session_store.update_session(
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session_entry.session_key,
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last_prompt_tokens=agent_result.get("last_prompt_tokens", 0),
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)
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return response
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|
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|
|
@ -1512,6 +1617,7 @@ class GatewayRunner:
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"`/usage` — Show token usage for this session",
|
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"`/insights [days]` — Show usage insights and analytics",
|
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"`/rollback [number]` — List or restore filesystem checkpoints",
|
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"`/background <prompt>` — Run a prompt in a separate background session",
|
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"`/reload-mcp` — Reload MCP servers from config",
|
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"`/update` — Update Hermes Agent to the latest version",
|
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"`/help` — Show this message",
|
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|
|
@ -1745,14 +1851,39 @@ class GatewayRunner:
|
|||
|
||||
if not args:
|
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lines = ["🎭 **Available Personalities**\n"]
|
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lines.append("• `none` — (no personality overlay)")
|
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for name, prompt in personalities.items():
|
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preview = prompt[:50] + "..." if len(prompt) > 50 else prompt
|
||||
if isinstance(prompt, dict):
|
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preview = prompt.get("description") or prompt.get("system_prompt", "")[:50]
|
||||
else:
|
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preview = prompt[:50] + "..." if len(prompt) > 50 else prompt
|
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lines.append(f"• `{name}` — {preview}")
|
||||
lines.append(f"\nUsage: `/personality <name>`")
|
||||
return "\n".join(lines)
|
||||
|
||||
if args in personalities:
|
||||
new_prompt = personalities[args]
|
||||
def _resolve_prompt(value):
|
||||
if isinstance(value, dict):
|
||||
parts = [value.get("system_prompt", "")]
|
||||
if value.get("tone"):
|
||||
parts.append(f'Tone: {value["tone"]}')
|
||||
if value.get("style"):
|
||||
parts.append(f'Style: {value["style"]}')
|
||||
return "\n".join(p for p in parts if p)
|
||||
return str(value)
|
||||
|
||||
if args in ("none", "default", "neutral"):
|
||||
try:
|
||||
if "agent" not in config or not isinstance(config.get("agent"), dict):
|
||||
config["agent"] = {}
|
||||
config["agent"]["system_prompt"] = ""
|
||||
with open(config_path, "w") as f:
|
||||
yaml.dump(config, f, default_flow_style=False, sort_keys=False)
|
||||
except Exception as e:
|
||||
return f"⚠️ Failed to save personality change: {e}"
|
||||
self._ephemeral_system_prompt = ""
|
||||
return "🎭 Personality cleared — using base agent behavior.\n_(takes effect on next message)_"
|
||||
elif args in personalities:
|
||||
new_prompt = _resolve_prompt(personalities[args])
|
||||
|
||||
# Write to config.yaml, same pattern as CLI save_config_value.
|
||||
try:
|
||||
|
|
@ -1769,7 +1900,7 @@ class GatewayRunner:
|
|||
|
||||
return f"🎭 Personality set to **{args}**\n_(takes effect on next message)_"
|
||||
|
||||
available = ", ".join(f"`{n}`" for n in personalities.keys())
|
||||
available = "`none`, " + ", ".join(f"`{n}`" for n in personalities.keys())
|
||||
return f"Unknown personality: `{args}`\n\nAvailable: {available}"
|
||||
|
||||
async def _handle_retry_command(self, event: MessageEvent) -> str:
|
||||
|
|
@ -1793,6 +1924,8 @@ class GatewayRunner:
|
|||
# Truncate history to before the last user message and persist
|
||||
truncated = history[:last_user_idx]
|
||||
self.session_store.rewrite_transcript(session_entry.session_id, truncated)
|
||||
# Reset stored token count — transcript was truncated
|
||||
session_entry.last_prompt_tokens = 0
|
||||
|
||||
# Re-send by creating a fake text event with the old message
|
||||
retry_event = MessageEvent(
|
||||
|
|
@ -1824,6 +1957,8 @@ class GatewayRunner:
|
|||
removed_msg = history[last_user_idx].get("content", "")
|
||||
removed_count = len(history) - last_user_idx
|
||||
self.session_store.rewrite_transcript(session_entry.session_id, history[:last_user_idx])
|
||||
# Reset stored token count — transcript was truncated
|
||||
session_entry.last_prompt_tokens = 0
|
||||
|
||||
preview = removed_msg[:40] + "..." if len(removed_msg) > 40 else removed_msg
|
||||
return f"↩️ Undid {removed_count} message(s).\nRemoved: \"{preview}\""
|
||||
|
|
@ -1917,6 +2052,197 @@ class GatewayRunner:
|
|||
)
|
||||
return f"❌ {result['error']}"
|
||||
|
||||
async def _handle_background_command(self, event: MessageEvent) -> str:
|
||||
"""Handle /background <prompt> — run a prompt in a separate background session.
|
||||
|
||||
Spawns a new AIAgent in a background thread with its own session.
|
||||
When it completes, sends the result back to the same chat without
|
||||
modifying the active session's conversation history.
|
||||
"""
|
||||
prompt = event.get_command_args().strip()
|
||||
if not prompt:
|
||||
return (
|
||||
"Usage: /background <prompt>\n"
|
||||
"Example: /background Summarize the top HN stories today\n\n"
|
||||
"Runs the prompt in a separate session. "
|
||||
"You can keep chatting — the result will appear here when done."
|
||||
)
|
||||
|
||||
source = event.source
|
||||
task_id = f"bg_{datetime.now().strftime('%H%M%S')}_{os.urandom(3).hex()}"
|
||||
|
||||
# Fire-and-forget the background task
|
||||
asyncio.create_task(
|
||||
self._run_background_task(prompt, source, task_id)
|
||||
)
|
||||
|
||||
preview = prompt[:60] + ("..." if len(prompt) > 60 else "")
|
||||
return f'🔄 Background task started: "{preview}"\nTask ID: {task_id}\nYou can keep chatting — results will appear when done.'
|
||||
|
||||
async def _run_background_task(
|
||||
self, prompt: str, source: "SessionSource", task_id: str
|
||||
) -> None:
|
||||
"""Execute a background agent task and deliver the result to the chat."""
|
||||
from run_agent import AIAgent
|
||||
|
||||
adapter = self.adapters.get(source.platform)
|
||||
if not adapter:
|
||||
logger.warning("No adapter for platform %s in background task %s", source.platform, task_id)
|
||||
return
|
||||
|
||||
_thread_metadata = {"thread_id": source.thread_id} if source.thread_id else None
|
||||
|
||||
try:
|
||||
runtime_kwargs = _resolve_runtime_agent_kwargs()
|
||||
if not runtime_kwargs.get("api_key"):
|
||||
await adapter.send(
|
||||
source.chat_id,
|
||||
f"❌ Background task {task_id} failed: no provider credentials configured.",
|
||||
metadata=_thread_metadata,
|
||||
)
|
||||
return
|
||||
|
||||
# Read model from config via shared helper
|
||||
model = _resolve_gateway_model()
|
||||
|
||||
# Determine toolset (same logic as _run_agent)
|
||||
default_toolset_map = {
|
||||
Platform.LOCAL: "hermes-cli",
|
||||
Platform.TELEGRAM: "hermes-telegram",
|
||||
Platform.DISCORD: "hermes-discord",
|
||||
Platform.WHATSAPP: "hermes-whatsapp",
|
||||
Platform.SLACK: "hermes-slack",
|
||||
Platform.SIGNAL: "hermes-signal",
|
||||
Platform.HOMEASSISTANT: "hermes-homeassistant",
|
||||
Platform.EMAIL: "hermes-email",
|
||||
}
|
||||
platform_toolsets_config = {}
|
||||
try:
|
||||
config_path = _hermes_home / 'config.yaml'
|
||||
if config_path.exists():
|
||||
import yaml
|
||||
with open(config_path, 'r', encoding="utf-8") as f:
|
||||
user_config = yaml.safe_load(f) or {}
|
||||
platform_toolsets_config = user_config.get("platform_toolsets", {})
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
platform_config_key = {
|
||||
Platform.LOCAL: "cli",
|
||||
Platform.TELEGRAM: "telegram",
|
||||
Platform.DISCORD: "discord",
|
||||
Platform.WHATSAPP: "whatsapp",
|
||||
Platform.SLACK: "slack",
|
||||
Platform.SIGNAL: "signal",
|
||||
Platform.HOMEASSISTANT: "homeassistant",
|
||||
Platform.EMAIL: "email",
|
||||
}.get(source.platform, "telegram")
|
||||
|
||||
config_toolsets = platform_toolsets_config.get(platform_config_key)
|
||||
if config_toolsets and isinstance(config_toolsets, list):
|
||||
enabled_toolsets = config_toolsets
|
||||
else:
|
||||
default_toolset = default_toolset_map.get(source.platform, "hermes-telegram")
|
||||
enabled_toolsets = [default_toolset]
|
||||
|
||||
platform_key = "cli" if source.platform == Platform.LOCAL else source.platform.value
|
||||
|
||||
pr = self._provider_routing
|
||||
max_iterations = int(os.getenv("HERMES_MAX_ITERATIONS", "90"))
|
||||
|
||||
def run_sync():
|
||||
agent = AIAgent(
|
||||
model=model,
|
||||
**runtime_kwargs,
|
||||
max_iterations=max_iterations,
|
||||
quiet_mode=True,
|
||||
verbose_logging=False,
|
||||
enabled_toolsets=enabled_toolsets,
|
||||
reasoning_config=self._reasoning_config,
|
||||
providers_allowed=pr.get("only"),
|
||||
providers_ignored=pr.get("ignore"),
|
||||
providers_order=pr.get("order"),
|
||||
provider_sort=pr.get("sort"),
|
||||
provider_require_parameters=pr.get("require_parameters", False),
|
||||
provider_data_collection=pr.get("data_collection"),
|
||||
session_id=task_id,
|
||||
platform=platform_key,
|
||||
session_db=self._session_db,
|
||||
fallback_model=self._fallback_model,
|
||||
)
|
||||
|
||||
return agent.run_conversation(
|
||||
user_message=prompt,
|
||||
task_id=task_id,
|
||||
)
|
||||
|
||||
loop = asyncio.get_event_loop()
|
||||
result = await loop.run_in_executor(None, run_sync)
|
||||
|
||||
response = result.get("final_response", "") if result else ""
|
||||
if not response and result and result.get("error"):
|
||||
response = f"Error: {result['error']}"
|
||||
|
||||
# Extract media files from the response
|
||||
if response:
|
||||
media_files, response = adapter.extract_media(response)
|
||||
images, text_content = adapter.extract_images(response)
|
||||
|
||||
preview = prompt[:60] + ("..." if len(prompt) > 60 else "")
|
||||
header = f'✅ Background task complete\nPrompt: "{preview}"\n\n'
|
||||
|
||||
if text_content:
|
||||
await adapter.send(
|
||||
chat_id=source.chat_id,
|
||||
content=header + text_content,
|
||||
metadata=_thread_metadata,
|
||||
)
|
||||
elif not images and not media_files:
|
||||
await adapter.send(
|
||||
chat_id=source.chat_id,
|
||||
content=header + "(No response generated)",
|
||||
metadata=_thread_metadata,
|
||||
)
|
||||
|
||||
# Send extracted images
|
||||
for image_url, alt_text in (images or []):
|
||||
try:
|
||||
await adapter.send_image(
|
||||
chat_id=source.chat_id,
|
||||
image_url=image_url,
|
||||
caption=alt_text,
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Send media files
|
||||
for media_path in (media_files or []):
|
||||
try:
|
||||
await adapter.send_file(
|
||||
chat_id=source.chat_id,
|
||||
file_path=media_path,
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
else:
|
||||
preview = prompt[:60] + ("..." if len(prompt) > 60 else "")
|
||||
await adapter.send(
|
||||
chat_id=source.chat_id,
|
||||
content=f'✅ Background task complete\nPrompt: "{preview}"\n\n(No response generated)',
|
||||
metadata=_thread_metadata,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.exception("Background task %s failed", task_id)
|
||||
try:
|
||||
await adapter.send(
|
||||
chat_id=source.chat_id,
|
||||
content=f"❌ Background task {task_id} failed: {e}",
|
||||
metadata=_thread_metadata,
|
||||
)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
async def _handle_compress_command(self, event: MessageEvent) -> str:
|
||||
"""Handle /compress command -- manually compress conversation context."""
|
||||
source = event.source
|
||||
|
|
@ -1934,6 +2260,9 @@ class GatewayRunner:
|
|||
if not runtime_kwargs.get("api_key"):
|
||||
return "No provider configured -- cannot compress."
|
||||
|
||||
# Resolve model from config (same reason as memory flush above).
|
||||
model = _resolve_gateway_model()
|
||||
|
||||
msgs = [
|
||||
{"role": m.get("role"), "content": m.get("content")}
|
||||
for m in history
|
||||
|
|
@ -1944,6 +2273,7 @@ class GatewayRunner:
|
|||
|
||||
tmp_agent = AIAgent(
|
||||
**runtime_kwargs,
|
||||
model=model,
|
||||
max_iterations=4,
|
||||
quiet_mode=True,
|
||||
enabled_toolsets=["memory"],
|
||||
|
|
@ -1957,6 +2287,10 @@ class GatewayRunner:
|
|||
)
|
||||
|
||||
self.session_store.rewrite_transcript(session_entry.session_id, compressed)
|
||||
# Reset stored token count — transcript changed, old value is stale
|
||||
self.session_store.update_session(
|
||||
session_entry.session_key, last_prompt_tokens=0,
|
||||
)
|
||||
new_count = len(compressed)
|
||||
new_tokens = estimate_messages_tokens_rough(compressed)
|
||||
|
||||
|
|
@ -2600,6 +2934,7 @@ class GatewayRunner:
|
|||
Platform.SLACK: "hermes-slack",
|
||||
Platform.SIGNAL: "hermes-signal",
|
||||
Platform.HOMEASSISTANT: "hermes-homeassistant",
|
||||
Platform.EMAIL: "hermes-email",
|
||||
}
|
||||
|
||||
# Try to load platform_toolsets from config
|
||||
|
|
@ -2623,6 +2958,7 @@ class GatewayRunner:
|
|||
Platform.SLACK: "slack",
|
||||
Platform.SIGNAL: "signal",
|
||||
Platform.HOMEASSISTANT: "homeassistant",
|
||||
Platform.EMAIL: "email",
|
||||
}.get(source.platform, "telegram")
|
||||
|
||||
# Use config override if present (list of toolsets), otherwise hardcoded default
|
||||
|
|
@ -2776,7 +3112,7 @@ class GatewayRunner:
|
|||
|
||||
# Restore typing indicator
|
||||
await asyncio.sleep(0.3)
|
||||
await adapter.send_typing(source.chat_id)
|
||||
await adapter.send_typing(source.chat_id, metadata=_progress_metadata)
|
||||
|
||||
except queue.Empty:
|
||||
await asyncio.sleep(0.3)
|
||||
|
|
@ -2854,21 +3190,7 @@ class GatewayRunner:
|
|||
except Exception:
|
||||
pass
|
||||
|
||||
model = os.getenv("HERMES_MODEL") or os.getenv("LLM_MODEL") or "anthropic/claude-opus-4.6"
|
||||
|
||||
try:
|
||||
import yaml as _y
|
||||
_cfg_path = _hermes_home / "config.yaml"
|
||||
if _cfg_path.exists():
|
||||
with open(_cfg_path, encoding="utf-8") as _f:
|
||||
_cfg = _y.safe_load(_f) or {}
|
||||
_model_cfg = _cfg.get("model", {})
|
||||
if isinstance(_model_cfg, str):
|
||||
model = _model_cfg
|
||||
elif isinstance(_model_cfg, dict):
|
||||
model = _model_cfg.get("default", model)
|
||||
except Exception:
|
||||
pass
|
||||
model = _resolve_gateway_model()
|
||||
|
||||
try:
|
||||
runtime_kwargs = _resolve_runtime_agent_kwargs()
|
||||
|
|
@ -2974,6 +3296,13 @@ class GatewayRunner:
|
|||
|
||||
# Return final response, or a message if something went wrong
|
||||
final_response = result.get("final_response")
|
||||
|
||||
# Extract last actual prompt token count from the agent's compressor
|
||||
_last_prompt_toks = 0
|
||||
_agent = agent_holder[0]
|
||||
if _agent and hasattr(_agent, "context_compressor"):
|
||||
_last_prompt_toks = getattr(_agent.context_compressor, "last_prompt_tokens", 0)
|
||||
|
||||
if not final_response:
|
||||
error_msg = f"⚠️ {result['error']}" if result.get("error") else "(No response generated)"
|
||||
return {
|
||||
|
|
@ -2982,6 +3311,7 @@ class GatewayRunner:
|
|||
"api_calls": result.get("api_calls", 0),
|
||||
"tools": tools_holder[0] or [],
|
||||
"history_offset": len(agent_history),
|
||||
"last_prompt_tokens": _last_prompt_toks,
|
||||
}
|
||||
|
||||
# Scan tool results for MEDIA:<path> tags that need to be delivered
|
||||
|
|
@ -3025,6 +3355,7 @@ class GatewayRunner:
|
|||
"api_calls": result_holder[0].get("api_calls", 0) if result_holder[0] else 0,
|
||||
"tools": tools_holder[0] or [],
|
||||
"history_offset": len(agent_history),
|
||||
"last_prompt_tokens": _last_prompt_toks,
|
||||
}
|
||||
|
||||
# Start progress message sender if enabled
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue