fix: unify gateway session hygiene with agent compression config
The gateway had a SEPARATE compression system ('session hygiene')
with hardcoded thresholds (100k tokens / 200 messages) that were
completely disconnected from the model's context length and the
user's compression config in config.yaml. This caused premature
auto-compression on Telegram/Discord — triggering at ~60k tokens
(from the 200-message threshold) or inconsistent token counts.
Changes:
- Gateway hygiene now reads model name from config.yaml and uses
get_model_context_length() to derive the actual context limit
- Compression threshold comes from compression.threshold in
config.yaml (default 0.85), same as the agent's ContextCompressor
- Removed the message-count-based trigger (was redundant and caused
false positives in tool-heavy sessions)
- Removed the undocumented session_hygiene config section — the
standard compression.* config now controls everything
- Env var overrides (CONTEXT_COMPRESSION_THRESHOLD,
CONTEXT_COMPRESSION_ENABLED) are respected
- Warn threshold is now 95% of model context (was hardcoded 200k)
- Updated tests to verify model-aware thresholds, scaling across
models, and that message count alone no longer triggers compression
For claude-opus-4.6 (200k context) at 85% threshold: gateway
hygiene now triggers at 170k tokens instead of the old 100k.
This commit is contained in:
teknium1
parent
3ffaac00dd
commit
67275641f8
2 changed files with 253 additions and 180 deletions
278
gateway/run.py
278
gateway/run.py
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@ -900,159 +900,187 @@ class GatewayRunner:
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# every new message rehydrates an oversized transcript, causing
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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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# -----------------------------------------------------------------
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if history and len(history) >= 4:
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from agent.model_metadata import estimate_messages_tokens_rough
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from agent.model_metadata import (
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estimate_messages_tokens_rough,
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get_model_context_length,
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)
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# Read thresholds from config.yaml → session_hygiene section
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_hygiene_cfg = {}
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# Read model + compression config from config.yaml — same
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# source of truth the agent itself uses.
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_hyg_model = "anthropic/claude-sonnet-4.6"
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_hyg_threshold_pct = 0.85
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_hyg_compression_enabled = True
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try:
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_hyg_cfg_path = _hermes_home / "config.yaml"
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if _hyg_cfg_path.exists():
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import yaml as _hyg_yaml
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with open(_hyg_cfg_path) as _hyg_f:
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_hyg_data = _hyg_yaml.safe_load(_hyg_f) or {}
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_hygiene_cfg = _hyg_data.get("session_hygiene", {})
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if not isinstance(_hygiene_cfg, dict):
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_hygiene_cfg = {}
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# Resolve model name (same logic as run_sync)
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_model_cfg = _hyg_data.get("model", {})
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if isinstance(_model_cfg, str):
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_hyg_model = _model_cfg
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elif isinstance(_model_cfg, dict):
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_hyg_model = _model_cfg.get("default", _hyg_model)
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# Read compression settings
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_comp_cfg = _hyg_data.get("compression", {})
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if isinstance(_comp_cfg, dict):
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_hyg_threshold_pct = float(
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_comp_cfg.get("threshold", _hyg_threshold_pct)
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)
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_hyg_compression_enabled = str(
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_comp_cfg.get("enabled", True)
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).lower() in ("true", "1", "yes")
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except Exception:
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pass
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_compress_token_threshold = int(
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_hygiene_cfg.get("auto_compress_tokens", 100_000)
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)
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_compress_msg_threshold = int(
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_hygiene_cfg.get("auto_compress_messages", 200)
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)
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_warn_token_threshold = int(
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_hygiene_cfg.get("warn_tokens", 200_000)
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# Also check env overrides (same as run_agent.py)
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_hyg_threshold_pct = float(
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os.getenv("CONTEXT_COMPRESSION_THRESHOLD", str(_hyg_threshold_pct))
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)
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if os.getenv("CONTEXT_COMPRESSION_ENABLED", "").lower() in ("false", "0", "no"):
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_hyg_compression_enabled = False
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_msg_count = len(history)
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_approx_tokens = estimate_messages_tokens_rough(history)
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_needs_compress = (
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_approx_tokens >= _compress_token_threshold
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or _msg_count >= _compress_msg_threshold
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)
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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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"(thresholds: %s msgs / %s tokens)",
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_msg_count, f"{_approx_tokens:,}",
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_compress_msg_threshold, f"{_compress_token_threshold:,}",
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if _hyg_compression_enabled:
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_hyg_context_length = get_model_context_length(_hyg_model)
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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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_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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"(threshold: %s%% of %s = %s tokens)",
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_msg_count, f"{_approx_tokens:,}",
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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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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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)
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except Exception:
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pass
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_hyg_adapter = self.adapters.get(source.platform)
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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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)
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except Exception:
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pass
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from run_agent import AIAgent
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try:
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from run_agent import AIAgent
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_hyg_runtime = _resolve_runtime_agent_kwargs()
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if _hyg_runtime.get("api_key"):
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_hyg_msgs = [
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{"role": m.get("role"), "content": m.get("content")}
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for m in history
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if m.get("role") in ("user", "assistant")
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and m.get("content")
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]
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_hyg_runtime = _resolve_runtime_agent_kwargs()
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if _hyg_runtime.get("api_key"):
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_hyg_msgs = [
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{"role": m.get("role"), "content": m.get("content")}
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for m in history
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if m.get("role") in ("user", "assistant")
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and m.get("content")
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]
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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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max_iterations=4,
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quiet_mode=True,
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enabled_toolsets=["memory"],
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session_id=session_entry.session_id,
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)
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loop = asyncio.get_event_loop()
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_compressed, _ = await loop.run_in_executor(
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None,
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lambda: _hyg_agent._compress_context(
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_hyg_msgs, "",
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approx_tokens=_approx_tokens,
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),
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)
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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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history = _compressed
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_new_count = len(_compressed)
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_new_tokens = estimate_messages_tokens_rough(
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_compressed
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)
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logger.info(
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"Session hygiene: compressed %s → %s msgs, "
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"~%s → ~%s tokens",
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_msg_count, _new_count,
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f"{_approx_tokens:,}", f"{_new_tokens:,}",
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)
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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"🗜️ 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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)
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except Exception:
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pass
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# Still too large after compression — warn user
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if _new_tokens >= _warn_token_threshold:
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logger.warning(
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"Session hygiene: still ~%s tokens after "
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"compression — suggesting /reset",
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f"{_new_tokens:,}",
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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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max_iterations=4,
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quiet_mode=True,
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enabled_toolsets=["memory"],
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session_id=session_entry.session_id,
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)
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loop = asyncio.get_event_loop()
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_compressed, _ = await loop.run_in_executor(
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None,
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lambda: _hyg_agent._compress_context(
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_hyg_msgs, "",
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approx_tokens=_approx_tokens,
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),
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)
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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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history = _compressed
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_new_count = len(_compressed)
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_new_tokens = estimate_messages_tokens_rough(
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_compressed
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)
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logger.info(
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"Session hygiene: compressed %s → %s msgs, "
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"~%s → ~%s tokens",
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_msg_count, _new_count,
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f"{_approx_tokens:,}", f"{_new_tokens:,}",
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)
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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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"⚠️ Session is still very large "
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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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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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)
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except Exception:
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pass
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except Exception as e:
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logger.warning(
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"Session hygiene auto-compress failed: %s", e
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)
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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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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 very large "
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f"({_msg_count} messages, "
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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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)
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except Exception:
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pass
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# Still too large after compression — warn user
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if _new_tokens >= _warn_token_threshold:
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logger.warning(
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"Session hygiene: still ~%s tokens after "
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"compression — suggesting /reset",
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f"{_new_tokens:,}",
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)
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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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"⚠️ Session is still very large "
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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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)
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except Exception:
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pass
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except Exception as e:
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logger.warning(
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"Session hygiene auto-compress failed: %s", e
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)
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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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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 very large "
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f"({_msg_count} messages, "
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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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)
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except Exception:
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pass
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# First-message onboarding -- only on the very first interaction ever
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if not history and not self.session_store.has_any_sessions():
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