Three modes: "none" (default, backward-compatible), "mentions" (accept
bot messages only when they @mention us), "all" (accept all bot messages
except our own, to prevent echo loops).
Configurable via:
slack:
allow_bots: mentions
Or env var: SLACK_ALLOW_BOTS=mentions
Self-message guard always active regardless of mode.
Based on PR #3200 by Mibayy, adapted to current main with config.yaml
bridging support.
Fixes blockquote > escaping, edit_message raw markdown, ***bold italic***
handling, HTML entity double-escaping (&), Wikipedia URL parens
truncation, and step numbering format. Also adds format_message to the
tool-layer _send_to_platform for consistent formatting across all
delivery paths.
Changes:
- Protect Slack entities (<@user>, <https://...|label>, <!here>) from
escaping passes
- Protect blockquote > markers before HTML entity escaping
- Unescape-before-escape for idempotent HTML entity handling
- ***bold italic*** → *_text_* conversion (before **bold** pass)
- URL regex upgraded to handle balanced parentheses
- mrkdwn:True flag on chat_postMessage payloads
- format_message applied in edit_message and send_message_tool
- 52 new tests (format, edit, streaming, splitting, tool chunking)
- Use reversed(dict) idiom for placeholder restoration
Based on PR #3715 by dashed, cherry-picked onto current main.
Port the mention gating pattern from Telegram, Discord, WhatsApp, and
Matrix adapters to the Slack platform adapter.
- Add _slack_require_mention() with explicit-false parsing and env var
fallback (SLACK_REQUIRE_MENTION)
- Add _slack_free_response_channels() with env var fallback
(SLACK_FREE_RESPONSE_CHANNELS)
- Replace hardcoded mention check with configurable gating logic
- Bridge slack config.yaml settings to env vars
- Bridge free_response_channels through the generic platform bridging loop
- Add 26 tests covering config parsing, env fallback, gating logic
Config usage:
slack:
require_mention: false
free_response_channels:
- "C0AQWDLHY9M"
Default behavior unchanged: channels require @mention (backward compatible).
Based on PR #5885 by dorukardahan, cherry-picked and adapted to current main.
Approval button clicks (Block Kit actions in Slack, CallbackQuery in
Telegram) bypass the normal message authorization flow in gateway/run.py.
Any workspace/group member who can see the approval message could click
Approve to authorize dangerous commands.
Read SLACK_ALLOWED_USERS / TELEGRAM_ALLOWED_USERS env vars directly in
the approval handlers. When an allowlist is configured and the clicking
user is not in it, the click is silently ignored (Slack) or answered
with an error (Telegram). Wildcard '*' permits all users. When no
allowlist is configured, behavior is unchanged (open access).
Based on the idea from PR #6735 by maymuneth, reimplemented to use the
existing env-var-based authorization system rather than a nonexistent
_allowed_user_ids adapter attribute.
1. gateway/platforms/slack.py: Replace check-then-set TOCTOU race on
_approval_resolved with atomic dict.pop(). Two concurrent button
clicks could both pass the guard before either set it to True,
causing double resolve_gateway_approval — which can resolve the
WRONG queued approval when multiple are pending for the same session.
2. hermes_state.py: Add WARNING log and proper fallbacks when
json.loads fails on tool_calls (→ []), reasoning_details (→ None),
and codex_reasoning_items (→ None). Previously, failures were
silently swallowed: tool_calls stayed as a raw string (iterating
yields characters, not objects), and reasoning fields were simply
missing from the dict.
Co-Authored-By: Claude Sonnet 4.6 (1M context) <noreply@anthropic.com>
Step 1 of _resolve_auto() explicitly excluded 'custom' providers,
forcing custom endpoint users through the fragile fallback chain
instead of using their known-working main model credentials.
This caused silent compression failures for users on local OpenAI-
compatible endpoints — the summary generation would fail, middle
turns would be silently dropped, and the agent would lose all
conversation context.
Remove 'custom' from the exclusion list so custom endpoint users
get the same main-model-first treatment as DeepSeek, Anthropic,
Gemini, and other direct providers.
* fix(tests): mock is_safe_url in tests that use example.com
Tests using example.com URLs were failing because is_safe_url does a real DNS lookup which fails in environments where example.com doesn't resolve, causing the request to be blocked before reaching the already-mocked HTTP client. This should fix around 17 failing tests.
These tests test logic, caching, etc. so mocking this method should not modify them in any way. TestMattermostSendUrlAsFile was already doing this so we follow the same pattern.
* fix(test): use case-insensitive lookup for model context length check
DEFAULT_CONTEXT_LENGTHS uses inconsistent casing (MiniMax keys are lowercase, Qwen keys are mixed-case) so the test was broken in some cases since it couldn't find the model.
* fix(test): patch is_linux in systemd gateway restart test
The test only patched is_macos to False but didn't patch is_linux to True. On macOS hosts, is_linux() returns False and the systemd restart code path is skipped entirely, making the assertion fail.
* fix(test): use non-blocklisted env var in docker forward_env tests
GITHUB_TOKEN is in api_key_env_vars and thus in _HERMES_PROVIDER_ENV_BLOCKLIST so the env var is silently dropped, we replace it with a non-blocked one like DATABASE_URL so the tests actually work.
* fix(test): fully isolate _has_any_provider_configured from host env
_has_any_provider_configured() checks all env vars from PROVIDER_REGISTRY (not just the 5 the tests were clearing) and also calls get_auth_status() which detects gh auth token for Copilot. On machines with any of these set, the function returns True before reaching the code path under test.
Clear all registry vars and mock get_auth_status so host credentials don't interfere.
* fix(test): correct path to hermes_base_env.py in tool parser tests
Path(__file__).parent.parent resolved to tests/, not the project root.
The file lives at environments/hermes_base_env.py so we need one more parent level.
* fix(test): accept optional HTML fields in Matrix send payload
_send_matrix sometimes adds format and formatted_body when the markdown library is installed. The test was doing an exact dict equality check which broke. Check required fields instead.
* fix(test): add config.yaml to codex vision requirements test
The test only wrote auth.json but not config.yaml, so _read_main_provider() returned empty and vision auto-detect never tried the codex provider. Add a config.yaml pointing at openai-codex so the fallback path actually resolves the client.
* fix(test): clear OPENROUTER_API_KEY in _isolate_hermes_home
run_agent.py calls load_hermes_dotenv() at import time, which injects API keys from ~/.hermes/.env into os.environ before any test fixture runs. This caused test_agent_loop_tool_calling to make real API calls instead of skipping, which ends up making some tests fail.
* fix(test): add get_rate_limit_state to agent mock in usage report tests
_show_usage now calls agent.get_rate_limit_state() for rate limit
display. The SimpleNamespace mock was missing this method.
* fix(test): update expected Camofox config version from 12 to 13
* fix(test): mock _get_enabled_platforms in nous managed defaults test
Importing gateway.run leaks DISCORD_BOT_TOKEN into os.environ, which makes _get_enabled_platforms() return ["cli", "discord"] instead of just ["cli"]. tools_command loops per platform, so apply_nous_managed_defaults
runs twice: the first call sets config values, the second sees them as
already configured and returns an empty set, causing the assertion to
fail.
The setup wizard's OpenClaw migration previously ran immediately with
aggressive defaults (overwrite=True, preset=full) after a single
'Would you like to import?' prompt. This caused several problems:
- Config values with different semantics (e.g. tool_call_execution:
'auto' in OpenClaw vs 'off' for Hermes yolo mode) were imported
without translation
- Gateway tokens were hijacked from OpenClaw without warning, taking
over Telegram/Slack/Discord channels
- Instruction files (.md) containing OpenClaw-specific setup/restart
procedures were copied, causing Hermes restart failures
Now the migration:
1. Asks 'Would you like to see what can be imported?' (softer framing)
2. Runs a dry-run preview showing everything that would be imported
3. Displays categorized warnings for high-impact items (gateway
takeover, config value differences, instruction files)
4. Asks for explicit confirmation with default=No
5. Executes with overwrite=False (preserves existing Hermes config)
Also extracts _load_openclaw_migration_module() for reuse and adds
_print_migration_preview() with keyword-based warning detection.
Tests updated for two-phase behavior + new test for decline-after-preview.
When the API returns "max_tokens too large given prompt" (input tokens
are within the context window, but input + requested output > window),
the old code incorrectly routed through the same handler as "prompt too
long" errors, calling get_next_probe_tier() and permanently halving
context_length. This made things worse: the window was fine, only the
requested output size needed trimming for that one call.
Two distinct error classes now handled separately:
Prompt too long — input itself exceeds context window.
Fix: compress history + halve context_length (existing behaviour,
unchanged).
Output cap too large — input OK, but input + max_tokens > window.
Fix: parse available_tokens from the error message, set a one-shot
_ephemeral_max_output_tokens override for the retry, and leave
context_length completely untouched.
Changes:
- agent/model_metadata.py: add parse_available_output_tokens_from_error()
that detects Anthropic's "available_tokens: N" error format and returns
the available output budget, or None for all other error types.
- run_agent.py: call the new parser first in the is_context_length_error
block; if it fires, set _ephemeral_max_output_tokens (with a 64-token
safety margin) and break to retry without touching context_length.
_build_api_kwargs consumes the ephemeral value exactly once then clears
it so subsequent calls use self.max_tokens normally.
- agent/anthropic_adapter.py: expand build_anthropic_kwargs docstring to
clearly document the max_tokens (output cap) vs context_length (total
window) distinction, which is a persistent source of confusion due to
the OpenAI-inherited "max_tokens" name.
- cli-config.yaml.example: add inline comments explaining both keys side
by side where users are most likely to look.
- website/docs/integrations/providers.md: add a callout box at the top
of "Context Length Detection" and clarify the troubleshooting entry.
- tests/test_ctx_halving_fix.py: 24 tests across four classes covering
the parser, build_anthropic_kwargs clamping, ephemeral one-shot
consumption, and the invariant that context_length is never mutated
on output-cap errors.
/pr <anything> silently resolved to /prompt via the shortest-match
tiebreaker in prefix expansion, permanently overwriting the system
prompt and persisting to config. The command's functionality (setting
agent.system_prompt) is available via config.yaml and /personality
covers the common use case.
Removes: CommandDef, dispatch branch, _handle_prompt_command handler,
docs references, and updates subcommand extraction test.
list_authenticated_providers() was using env var names from the external
models.dev registry to detect credentials. This registry has incorrect
mappings for 5 providers: minimax-cn, zai, opencode-zen, opencode-go,
and kilocode — causing them to not appear in /model even when the
correct API key is set.
Now checks PROVIDER_REGISTRY from auth.py first (our source of truth),
falling back to models.dev only for providers not in our registry.
Fixes#6620. Based on devorun's investigation in PR #6625.
The error classifier's generic-400 heuristic only extracted err_body_msg from
the nested body structure (body['error']['message']), missing the flat body
format used by OpenAI's Responses API (body['message']). This caused
descriptive 400 errors like 'Invalid input[index].name: string does not match
pattern' to appear generic when the session was large, misclassifying them as
context overflow and triggering an infinite compression loop.
Added flat-body fallback in _classify_400() consistent with the parent
classify_api_error() function's existing handling at line 297-298.
The status bar reads self.model from the CLI class, which is set once
at init and never updated when _try_activate_fallback() switches to a
backup provider/model in run_agent.py. This causes the TUI to display
the original model name while context_length_max changes, creating a
confusing mismatch.
Read the model name from agent.model (live, updated by fallback) with
self.model as fallback before the agent is created. Remove the
redundant getattr(self, 'agent') call that was already done above.
When is explicitly set to ,
the custom-endpoint path in creates a plain
client without provider-specific headers. This means sync vision calls (e.g.
) use the generic User-Agent and get rejected by
Kimi's coding endpoint with a 403:
'Kimi For Coding is currently only available for Coding Agents such as Kimi CLI...'
The async converter already injects , and the
auto-detected API-key provider path also injects it, but the explicit custom
endpoint shortcut was missing it entirely.
This patch adds the same injection to the custom endpoint
branch, and updates all existing Kimi header sites to for
consistency.
Fixes <issue number to be filled in>
The credential pool seeder (_seed_from_env) hardcoded the base URL
for API-key providers without running provider-specific auto-detection.
For kimi-coding, this caused sk-kimi- prefixed keys to be seeded with
the legacy api.moonshot.ai/v1 endpoint instead of api.kimi.com/coding/v1,
resulting in HTTP 401 on the first request.
Import and call _resolve_kimi_base_url for kimi-coding so the pool
uses the correct endpoint based on the key prefix, matching the
runtime credential resolver behavior.
Also fix a comment: sk-kimi- keys are issued by kimi.com/code,
not platform.kimi.ai.
Fixes#5561
When _try_activate_fallback() swaps to a new provider (e.g.
kimi-coding), resolve_provider_client() correctly injects
provider-specific default_headers (like KimiCLI User-Agent) into the
returned OpenAI client. However, _client_kwargs was saved with only
api_key and base_url, dropping those headers.
Every subsequent API call rebuilds the client from _client_kwargs via
_create_request_openai_client(), producing a bare OpenAI client without
the required headers. Kimi Coding rejects this with 403; Copilot would
lose its auth headers similarly.
This patch reads _custom_headers from the fallback client (where the
OpenAI SDK stores the default_headers kwarg) and includes them in
_client_kwargs so any client rebuild preserves provider-specific headers.
Fixes#6075
Two bugs in the model fallback system:
1. Nous login leaves stale model in config (provider=nous, model=opus
from previous OpenRouter setup). Fixed by deferring the config.yaml
provider write until AFTER model selection completes, and passing the
selected model atomically via _update_config_for_provider's
default_model parameter. Previously, _update_config_for_provider was
called before model selection — if selection failed (free tier, no
models, exception), config stayed as nous+opus permanently.
2. Codex/stale providers in auxiliary fallback can't connect but block
the auto-detection chain. Added _is_connection_error() detection
(APIConnectionError, APITimeoutError, DNS failures, connection
refused) alongside the existing _is_payment_error() check in
call_llm(). When a provider endpoint is unreachable, the system now
falls back to the next available provider instead of crashing.
* fix(nix): switch nixpkgs input from nixos-24.11 to nixos-unstable
nixos-24.11 reached EOL on 2025-06-30. For a dev tool, tracking a
frozen release branch causes dependency versions to go stale.
nixos-unstable provides rolling updates and is the conventional
choice for development packages.
* docs(website): update nix flake example
---------
Co-authored-by: sk <sk@mercury>
* fix(ci): pin floating GitHub Actions tags and ascii-guard to explicit versions
Actions pinned to @main pull whatever is at that ref at execution time,
so a compromised upstream org could execute arbitrary code in CI.
- Pin DeterminateSystems/nix-installer-action to commit SHA (v22)
- Pin DeterminateSystems/magic-nix-cache-action to commit SHA (v13)
- Pin ascii-guard to 2.3.0 in docs-site-checks workflow
SHA comments include the version tag for human readability; Renovate or
Dependabot can keep these updated automatically.
* Add skill metadata extraction step in workflow
Add step to extract skill metadata for dashboard in CI workflow.
---------
Co-authored-by: Siddharth Balyan <52913345+alt-glitch@users.noreply.github.com>
Every turn now logs WHY the agent loop ended to agent.log with a
structured INFO line capturing: exit reason, model, api_calls/max,
budget usage, tool turn count, last message role, response length,
and session ID.
When the last message is a tool result and the turn was NOT
interrupted, emits WARNING level (visible in errors.log) — this is
the 'just stops' scenario users report where a tool call completes
but no continuation or final response follows.
10 tracked exit reasons: text_response, interrupted_by_user,
interrupted_during_api_call, budget_exhausted, max_iterations_reached,
all_retries_exhausted_no_response, fallback_prior_turn_content,
empty_response_exhausted, error_near_max_iterations, unknown.
Documents both debugging commands with full option tables,
examples, and usage guidance. Adds both to the top-level
commands table and as detailed sections with subsections for
log files, filtering behavior, and log rotation.
Adds a new CLI command that outputs a compact, plain-text dump of the
user's Hermes setup — version, OS, model/provider, API key presence,
toolsets, gateway status, platforms, cron jobs, skills, and any
non-default config overrides.
Designed for support context: no ANSI colors, ready to paste into
Discord/GitHub/Telegram. Secrets shown as 'set/not set' by default;
--show-keys reveals redacted prefixes (first/last 4 chars).
Files:
- hermes_cli/dump.py (new) — run_dump() implementation
- hermes_cli/main.py — parser + cmd_dump wiring
- hermes_cli/profiles.py — shell completions + subcommand set
The docs incorrectly referenced 'hermes pairing generate bluebubbles'
which doesn't exist. The existing reactive pairing flow already handles
this — when an unknown user messages the bot, it sends them a code
automatically, and the owner approves with 'hermes pairing approve'.
The old setup wizard (pre-March 2026) wrote LLM_MODEL to ~/.hermes/.env
across 12 provider flows. Commit 9302690e removed the writes but never
cleaned up existing .env files, leaving a dead variable that:
- Nothing in the codebase reads (zero os.getenv calls)
- The docs incorrectly claimed the gateway still used as fallback
- Caused user confusion when debugging model resolution issues
Changes:
- config.py: Bump _config_version 12 → 13, add migration to clear
LLM_MODEL and OPENAI_MODEL from .env (both dead since March 2026)
- environment-variables.md: Remove LLM_MODEL row, fix HERMES_MODEL
description to stop referencing it
- providers.md: Update deprecation notice from 'deprecated' to 'removed'
Parse x-ratelimit-* headers from inference API responses (Nous Portal,
OpenRouter, OpenAI-compatible) and display them in the /usage command.
- New agent/rate_limit_tracker.py: parse 12 rate limit headers (RPM/RPH/
TPM/TPH limits, remaining, reset timers), format as progress bars (CLI)
or compact one-liner (gateway)
- Hook into streaming path in run_agent.py: stream.response.headers is
available on the OpenAI SDK Stream object before chunks are consumed
- CLI /usage: appends rate limit section with progress bars + warnings
when any bucket exceeds 80%
- Gateway /usage: appends compact rate limit summary
- 24 unit tests covering parsing, formatting, edge cases
Headers captured per response:
x-ratelimit-{limit,remaining,reset}-{requests,tokens}{,-1h}
Example CLI display:
Nous Rate Limits (captured just now):
Requests/min [░░░░░░░░░░░░░░░░░░░░] 0.1% 1/800 used (799 left, resets in 59s)
Tokens/hr [░░░░░░░░░░░░░░░░░░░░] 0.0% 49/336.0M (336.0M left, resets in 52m)
Wrap is_dir() in _is_valid_subdir() and is_file() in
_load_hints_for_directory() with OSError handlers so that
inaccessible directories (e.g. /root from a non-root Daytona
host user) are silently skipped instead of crashing the agent.
The existing PermissionError PRs for prompt_builder.py (#6247,
#6321, #6355) do not cover subdirectory_hints.py, which was
identified as a separate crash path in the #6214 comments.
Ref: #6214
prune_sessions and delete_session only handled direct children when
satisfying the parent_session_id FK constraint. Multi-level chains
(A -> B -> C) caused IntegrityError because deleting B while C still
referenced it was blocked by the FK.
Fix: NULL out parent_session_id for any session whose parent is about
to be deleted. This orphans children instead of cascade-deleting them,
which also respects the prune retention window — newer child sessions
are no longer deleted just because an ancestor is old.
Reported by Aaryan2304 in PR #6463.
Updated the logic for determining the probed_url in the probe_api_models function to use the first tried URL instead of the last. This change ensures that the most relevant URL is returned when probing for models. Additionally, improved the output message in the _model_flow_custom function to provide clearer guidance based on the suggested_base_url.
The 24-hour default cooldown for 402-exhausted credentials was far too
aggressive — if a user tops up credits or the 402 was caused by an
oversized max_tokens request rather than true billing exhaustion, they
shouldn't have to wait a full day. Reduce to 1 hour (matching the
existing 429 TTL).
Inspired by PR #6493 (michalkomar).
When a model returns no content, no structured reasoning, and no tool
calls (common with open models), the agent now silently retries up to
3 times before falling through to (empty).
Silent retry (no synthetic messages) keeps the conversation history
clean, preserves prompt caching, and respects the no-synthetic-user-
injection invariant. Most empty responses from open models are
transient (provider hiccups, rate limits, sampling flukes) so a
simple retry is sufficient.
This fills the last gap in the empty-response recovery chain:
1. _last_content_with_tools fallback (prior tool turn had content)
2. Thinking-only prefill continuation (#5931 — structured reasoning)
3. Empty response silent retry (NEW — truly empty, no reasoning)
4. (empty) terminal (last resort after all retries exhausted)
Inline <think> blocks are excluded — the model chose to reason, it
just produced no visible text. That differs from truly empty.
Tests:
- Updated test_truly_empty to expect 4 API calls (1 + 3 retries)
- Added test_truly_empty_response_succeeds_on_nudge
The BlueBubbles adapter was merged but missing setup wizard support:
- Add _setup_bluebubbles() guided setup (server URL, password, allowlist,
home channel, webhook port)
- Add to _GATEWAY_PLATFORMS registry so it appears in 'hermes setup gateway'
- Add to any_messaging check and home channel missing warning
- Add to gateway status display in 'hermes setup'
- Add BLUEBUBBLES_SERVER_URL, BLUEBUBBLES_PASSWORD, BLUEBUBBLES_ALLOWED_USERS
to OPTIONAL_ENV_VARS with descriptions and categories
Previously the only way to configure BlueBubbles was manually editing .env.
Two issues resolved:
1. Add opencode.ai to _URL_TO_PROVIDER mapping so base_url routes through
models.dev lookup (which has mimo-v2-pro at 1M context) instead of
falling back to probing /models (404) and defaulting to 128K.
2. Fix _format_context_length to round cleanly: 1048576 → '1M' instead
of '1.048576M'. Applies same rounding logic to K values.
Add QEMU cross-compilation and multi-arch manifest support so Apple
Silicon (M1/M2/M3) and other ARM-based systems get native images.
- Add docker/setup-qemu-action for arm64 emulation on amd64 runners
- Smoke test stays amd64-only (load:true can't export multi-arch)
- Both push steps (main + release) now build linux/amd64,linux/arm64
- Bump timeout 30->60min for QEMU cross-compilation overhead
- Add permissions: contents: read (least-privilege hardening)
Salvaged from PR #3998 by Mibayy. Also addresses #5005 and #3913.
Co-authored-by: Mibayy <Mibayy@users.noreply.github.com>
Tests for the new behavior paths:
- Large tool outputs no longer block compaction (motivating scenario)
- Hard minimum of 3 tail messages always protected
- 1.5x soft ceiling for oversized messages
- Small conversations still compress (min 8 messages)
- Token-budget prune path in _prune_old_tool_results
- Fallback to message-count when no token budget
PR #6240 changed tail protection from protect_last_n to min(3, ...)
which increased the minimum compressible message count and shifted
tail boundaries. Three tests broke:
- test_summary_role_avoids_consecutive_user_messages: 6→8 msgs
- test_double_collision_user_head_assistant_tail: 7→8 msgs
- test_no_collision_scenarios_still_work: 6→8 msgs
All tests now exceed the new min_for_compress threshold (6) and
maintain proper role alternation in both head and tail sections.
Tail protection was effectively message-count based despite having a
token budget, because protect_last_n=20 acted as a hard floor. A single
50K-token tool output would cause all 20 recent messages to be
preserved regardless of budget, leaving little room for summarization.
Changes:
- _find_tail_cut_by_tokens: min_tail reduced from protect_last_n (20)
to 3; token budget is now the primary criterion
- Soft ceiling at 1.5x budget to avoid cutting mid-oversized-message
- _prune_old_tool_results: accepts optional protect_tail_tokens so
pruning also respects the token budget instead of a fixed count
- compress() minimum message check relaxed from protect_first_n +
protect_last_n + 1 to protect_first_n + 3 + 1
- Tool group alignment (no splitting tool_call/result) preserved
Port missing features from the hindsight-hermes external integration
package into the native plugin. Only touches plugin files — no core
changes.
Features:
- Tags on retain/recall (tags, recall_tags, recall_tags_match)
- Recall config (recall_max_tokens, recall_max_input_chars, recall_types,
recall_prompt_preamble)
- Retain controls (retain_every_n_turns, auto_retain, auto_recall,
retain_async via aretain_batch, retain_context)
- Bank config via Banks API (bank_mission, bank_retain_mission)
- Structured JSON retain with per-message timestamps
- Full session accumulation with document_id for dedup
- Custom post_setup() wizard with curses picker
- Mode-aware dep install (hindsight-client for cloud, hindsight-all for local)
- local_external mode and openai_compatible LLM provider
- OpenRouter support with auto base URL
- Auto-upgrade of hindsight-client to >=0.4.22 on session start
- Comprehensive debug logging across all operations
- 46 unit tests
- Updated README and website docs
Prevents unbounded memory growth in _assistant_threads dict.
Evicts oldest entries when exceeding _ASSISTANT_THREADS_MAX (5000),
matching the pattern used by _mentioned_threads and _seen_messages.
The test_non_internal_event_without_user_triggers_pairing test relied on
no Discord auth env vars being set, but gateway/run.py loads dotenv at
module level. In environments with DISCORD_ALLOW_ALL_USERS=True in .env,
the auth check passed instead of triggering the pairing flow.
Clear DISCORD_ALLOW_ALL_USERS, DISCORD_ALLOWED_USERS, GATEWAY_ALLOW_ALL_USERS,
and GATEWAY_ALLOWED_USERS via monkeypatch to ensure test isolation.
