Comprehensive cleanup across 80 files based on automated (ruff, pyflakes, vulture)
and manual analysis of the entire codebase.
Changes by category:
Unused imports removed (~95 across 55 files):
- Removed genuinely unused imports from all major subsystems
- agent/, hermes_cli/, tools/, gateway/, plugins/, cron/
- Includes imports in try/except blocks that were truly unused
(vs availability checks which were left alone)
Unused variables removed (~25):
- Removed dead variables: connected, inner, channels, last_exc,
source, new_server_names, verify, pconfig, default_terminal,
result, pending_handled, temperature, loop
- Dropped unused argparse subparser assignments in hermes_cli/main.py
(12 instances of add_parser() where result was never used)
Dead code removed:
- run_agent.py: Removed dead ternary (None if False else None) and
surrounding unreachable branch in identity fallback
- run_agent.py: Removed write-only attribute _last_reported_tool
- hermes_cli/providers.py: Removed dead @property decorator on
module-level function (decorator has no effect outside a class)
- gateway/run.py: Removed unused MCP config load before reconnect
- gateway/platforms/slack.py: Removed dead SessionSource construction
Undefined name bugs fixed (would cause NameError at runtime):
- batch_runner.py: Added missing logger = logging.getLogger(__name__)
- tools/environments/daytona.py: Added missing Dict and Path imports
Unnecessary global statements removed (14):
- tools/terminal_tool.py: 5 functions declared global for dicts
they only mutated via .pop()/[key]=value (no rebinding)
- tools/browser_tool.py: cleanup thread loop only reads flag
- tools/rl_training_tool.py: 4 functions only do dict mutations
- tools/mcp_oauth.py: only reads the global
- hermes_time.py: only reads cached values
Inefficient patterns fixed:
- startswith/endswith tuple form: 15 instances of
x.startswith('a') or x.startswith('b') consolidated to
x.startswith(('a', 'b'))
- len(x)==0 / len(x)>0: 13 instances replaced with pythonic
truthiness checks (not x / bool(x))
- in dict.keys(): 5 instances simplified to in dict
- Redefined unused name: removed duplicate _strip_mdv2 import in
send_message_tool.py
Other fixes:
- hermes_cli/doctor.py: Replaced undefined logger.debug() with pass
- hermes_cli/config.py: Consolidated chained .endswith() calls
Test results: 3934 passed, 17 failed (all pre-existing on main),
19 skipped. Zero regressions.
The AsyncOpenAI client was created once at __init__ and stored as an
instance attribute. process_directory() calls asyncio.run() which creates
and closes a fresh event loop. On a second call, the client's httpx
transport is still bound to the closed loop, raising RuntimeError:
"Event loop is closed" — the same pattern fixed by PR #3398 for the
main agent loop.
Create the client lazily in _get_async_client() so each asyncio.run()
gets a client bound to the current loop.
Co-authored-by: binhnt92 <binhnt.ht.92@gmail.com>
dict.get(key, default) returns None — not the default — when the key IS
present but explicitly set to null/~ in YAML. Calling .lower() on that
raises AttributeError.
Use (config.get(key) or fallback) so both missing keys and explicit nulls
coalesce to the intended default.
Files fixed:
- tools/tts_tool.py — _get_provider()
- tools/web_tools.py — _get_backend()
- tools/mcp_tool.py — MCPServerTask auth config
- trajectory_compressor.py — _detect_provider() and config loading
Co-authored-by: dieutx <dangtc94@gmail.com>
Normalize summary-model content before stripping so empty or non-string
responses do not trigger retry/fallback paths. Adds sync and async
regression tests for None content.
Add centralized call_llm() and async_call_llm() functions that own the
full LLM request lifecycle:
1. Resolve provider + model from task config or explicit args
2. Get or create a cached client for that provider
3. Format request args (max_tokens handling, provider extra_body)
4. Make the API call with max_tokens/max_completion_tokens retry
5. Return the response
Config: expanded auxiliary section with provider:model slots for all
tasks (compression, vision, web_extract, session_search, skills_hub,
mcp, flush_memories). Config version bumped to 7.
Migrated all auxiliary consumers:
- context_compressor.py: uses call_llm(task='compression')
- vision_tools.py: uses async_call_llm(task='vision')
- web_tools.py: uses async_call_llm(task='web_extract')
- session_search_tool.py: uses async_call_llm(task='session_search')
- browser_tool.py: uses call_llm(task='vision'/'web_extract')
- mcp_tool.py: uses call_llm(task='mcp')
- skills_guard.py: uses call_llm(provider='openrouter')
- run_agent.py flush_memories: uses call_llm(task='flush_memories')
Tests updated for context_compressor and MCP tool. Some test mocks
still need updating (15 remaining failures from mock pattern changes,
2 pre-existing).
Route all remaining ad-hoc auxiliary LLM call sites through
resolve_provider_client() so auth, headers, and API format (Chat
Completions vs Responses API) are handled consistently in one place.
Files changed:
- tools/openrouter_client.py: Replace manual AsyncOpenAI construction
with resolve_provider_client('openrouter', async_mode=True). The
shared client module now delegates entirely to the router.
- tools/skills_guard.py: Replace inline OpenAI client construction
(hardcoded OpenRouter base_url, manual api_key lookup, manual
headers) with resolve_provider_client('openrouter'). Remove unused
OPENROUTER_BASE_URL import.
- trajectory_compressor.py: Add _detect_provider() to map config
base_url to a provider name, then route through
resolve_provider_client. Falls back to raw construction for
unrecognized custom endpoints.
- mini_swe_runner.py: Route default case (no explicit api_key/base_url)
through resolve_provider_client('openrouter') with auto-detection
fallback. Preserves direct construction when explicit creds are
passed via CLI args.
- agent/auxiliary_client.py: Fix stale module docstring — vision auto
mode now correctly documents that Codex and custom endpoints are
tried (not skipped).
These two files were creating bare OpenAI clients pointing at OpenRouter
without the HTTP-Referer / X-OpenRouter-Title / X-OpenRouter-Categories
headers that the rest of the codebase sends for app attribution.
- skills_guard.py: LLM audit client (always OpenRouter)
- trajectory_compressor.py: sync + async summarization clients
(guarded with 'openrouter' in base_url check since the endpoint
is user-configurable)
- Updated `trajectory_compression.yaml` to include a new `per_trajectory_timeout` setting, allowing for a timeout of 300 seconds per trajectory. This enhancement helps prevent hanging on problematic entries during processing, improving overall reliability and efficiency in trajectory handling.
- Updated the main function to accept both single JSONL files and directories for compression.
- Added support for sampling a percentage of trajectories before compression.
- Improved usage documentation with detailed examples for various compression scenarios.
- Enhanced error handling for input validation and dry run mode.
- Streamlined output handling to manage temporary files during processing.
- Introduced mini_swe_runner.py for executing tasks using mini-swe-agent environments (local, Docker, Modal) and outputting trajectories in Hermes format.
- Implemented trajectory_compressor.py to post-process agent trajectories, compressing them within a target token budget while preserving essential content.
- Added trajectory_compression.yaml configuration file for customizable compression settings.
- Created sample_and_compress.py script to download, sample, and compress trajectories from HuggingFace datasets.
- Enhanced logging and error handling across new modules for improved usability and debugging.
