Three categories of cleanup, all zero-behavioral-change:
1. F-strings without placeholders (154 fixes across 29 files)
- Converted f'...' to '...' where no {expression} was present
- Heaviest files: run_agent.py (24), cli.py (20), honcho_integration/cli.py (34)
2. Simplify defensive patterns in run_agent.py
- Added explicit self._is_anthropic_oauth = False in __init__ (before
the api_mode branch that conditionally sets it)
- Replaced 7x getattr(self, '_is_anthropic_oauth', False) with direct
self._is_anthropic_oauth (attribute always initialized now)
- Added _is_openrouter_url() and _is_anthropic_url() helper methods
- Replaced 3 inline 'openrouter' in self._base_url_lower checks
3. Remove dead code in small files
- hermes_cli/claw.py: removed unused 'total' computation
- tools/fuzzy_match.py: removed unused strip_indent() function and
pattern_stripped variable
Full test suite: 6184 passed, 0 failures
E2E PTY: banner clean, tool calls work, zero garbled ANSI
Replace all minisweagent imports with Hermes-Agent's own environment
classes (LocalEnvironment, DockerEnvironment, ModalEnvironment).
mini_swe_runner.py no longer has any dependency on mini-swe-agent.
The runner now uses the same backends as the terminal tool, so Docker
and Modal environments work out of the box without extra submodules.
Tested: local and Docker backends verified working through the runner.
Drop the mini-swe-agent git submodule. All terminal backends now use
hermes-agent's own environment implementations directly.
Docker backend:
- Inline the `docker run -d` container startup (was 15 lines in
minisweagent's DockerEnvironment). Our wrapper already handled
execute(), cleanup(), security hardening, volumes, and resource limits.
Modal backend:
- Import swe-rex's ModalDeployment directly instead of going through
minisweagent's 90-line passthrough wrapper.
- Bake the _AsyncWorker pattern (from environments/patches.py) directly
into ModalEnvironment for Atropos compatibility without monkey-patching.
Cleanup:
- Remove minisweagent_path.py (submodule path resolution helper)
- Remove submodule init/install from install.sh and setup-hermes.sh
- Remove mini-swe-agent from .gitmodules
- environments/patches.py is now a no-op (kept for backward compat)
- terminal_tool.py no longer does sys.path hacking for minisweagent
- mini_swe_runner.py guards imports (optional, for RL training only)
- Update all affected tests to mock the new direct subprocess calls
- Update README.md, CONTRIBUTING.md
No functionality change — all Docker, Modal, local, SSH, Singularity,
and Daytona backends behave identically. 6093 tests pass.
Salvage of PR #1246 by ChatGPT (teknium1 session), resolved against
current main which already includes #1239.
Changes:
- Add minisweagent_path.py: worktree-aware helper that finds
mini-swe-agent/src from either the current checkout or the main
checkout behind a git worktree
- Use the helper in tools/terminal_tool.py and mini_swe_runner.py
instead of naive path-relative lookup that fails in worktrees
- Clean up check_terminal_requirements():
- local: return True (no minisweagent dep, per #1239)
- singularity/ssh: remove unnecessary minisweagent imports
- docker/modal: use importlib.util.find_spec with clear error
- Add regression tests for worktree path discovery and tool resolution
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).
Removed the hard block on base_url containing 'api.anthropic.com'.
Anthropic now offers an OpenAI-compatible /chat/completions endpoint,
so blocking their URL prevents legitimate use. If the endpoint isn't
compatible, the API call will fail with a proper error anyway.
Removed from: run_agent.py, mini_swe_runner.py
Updated test to verify Anthropic URLs are accepted.
Updated the default model version from "anthropic/claude-sonnet-4-20250514" to "anthropic/claude-sonnet-4.6" across multiple files including AGENTS.md, batch_runner.py, mini_swe_runner.py, and run_agent.py for consistency and to reflect the latest model improvements.
- Updated `.env.example` to include new API keys and configuration options for the mini-swe-agent backend, including support for local, Docker, and Modal environments.
- Added `.gitmodules` to include mini-swe-agent as a submodule for easier integration.
- Refactored `mini_swe_runner.py` to use the updated model format and default to OpenRouter for API calls.
- Enhanced `model_tools.py` to support the new terminal tool definitions and ensure compatibility with the mini-swe-agent backend.
- Updated `README.md` to reflect changes in setup instructions and environment variable configurations.
- Improved `terminal_tool.py` to manage execution environments and lifecycle, ensuring proper cleanup and error handling.
- Introduced `terminal_hecate.py` for executing commands on MorphCloud VMs, providing an alternative backend for terminal operations.
- 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.
