Plugin hooks fired after a tool dispatch now receive an integer
duration_ms kwarg measuring how long the tool's registry.dispatch()
call took (time.monotonic() before/after). Inspired by Claude Code
2.1.119 which added the same field to PostToolUse hook inputs.
Wire points:
- model_tools.py: measure dispatch latency, pass duration_ms to
invoke_hook("post_tool_call", ...) and invoke_hook("transform_tool_result", ...)
- hermes_cli/hooks.py: include duration_ms in the synthetic payload
used by 'hermes hooks test' and 'hermes hooks doctor' so shell-hook
authors see the same shape at development time as runtime
- shell hooks (agent/shell_hooks.py): no code change needed;
_serialize_payload already surfaces non-top-level kwargs under
payload['extra'], so duration_ms lands at extra.duration_ms for
shell-hook scripts
Plugin authors can now build latency dashboards, per-tool SLO alerts,
and regression canaries without having to wrap every tool manually.
Test: tests/test_model_tools.py::test_post_tool_call_receives_non_negative_integer_duration_ms
E2E: real PluginManager + dispatch monkey-patched with a 50ms sleep,
hook callback observes duration_ms=50 (int).
Refs: https://code.claude.com/docs/en/changelog (2.1.119, Apr 23 2026)
Adds a floor below --yolo: a tiny set of commands so catastrophic they
should never run via the agent, regardless of --yolo, gateway /yolo,
approvals.mode=off, or cron approve mode. Opting into yolo is trusting
the agent with your files and services — not trusting it to wipe the
disk or power the box off.
The list is deliberately small (12 patterns), covering only
unrecoverable ops:
- rm -rf targeting /, /home, /etc, /usr, /var, /boot, /bin, /sbin,
/lib, ~, $HOME
- mkfs (any variant)
- dd + redirection to raw block devices (/dev/sd*, /dev/nvme*, etc.)
- fork bomb
- kill -1 / kill -9 -1
- shutdown, reboot, halt, poweroff, init 0/6, telinit 0/6,
systemctl poweroff/reboot/halt/kexec
Recoverable-but-costly commands (git reset --hard, rm -rf /tmp/x,
chmod -R 777, curl | sh) stay in DANGEROUS_PATTERNS where yolo can
still pass them through — that's what yolo is for.
Container backends (docker/singularity/modal/daytona) continue to
bypass both hardline and dangerous checks, since nothing they do can
touch the host.
Inspired by Mercury Agent's permission-hardened blocklist.
Bare `hermes setup` on a returning user now drops straight into the
full reconfigure wizard — every prompt shows the current value as its
default, press Enter to keep or type a new value to change it. The
returning-user menu is gone.
Behavior:
- First-time user: first-time wizard (unchanged)
- Returning user, bare command: full reconfigure wizard (new default)
- Returning user, `--quick`: only prompt for missing/unset items
- Returning user, one section: `hermes setup model|terminal|gateway|tools|agent`
- `--reconfigure`: preserved as backwards-compat alias (no-op since it's now default)
The section functions already used current values as prompt defaults —
this change just removes the extra click to get to them.
The 'Quick Setup - configure missing items only' menu option is now
exposed as the explicit `--quick` flag; it's the narrow case of
filling in missing config (e.g. after a partial OpenClaw migration or
when a required API key got cleared).
Inspired by Mercury Agent's `mercury doctor` UX.
Also removes:
- RETURNING_USER_MENU_SECTION_KEYS (orphaned constant)
- Two returning-user menu tests in test_setup_noninteractive.py
(guarding behavior that no longer exists — covered by
test_setup_reconfigure.py instead)
- New website/docs/guides/azure-foundry.md covering both OpenAI-style
and Anthropic-style endpoints, auto-detection behaviour, gpt-5.x
routing, /v1 stripping, api-version query forwarding, and the
provider: anthropic + Azure URL alternative setup.
- environment-variables.md picks up AZURE_FOUNDRY_API_KEY,
AZURE_FOUNDRY_BASE_URL, AZURE_ANTHROPIC_KEY.
- cli-commands.md includes azure-foundry in the provider choices list.
- configuration.md lists azure-foundry among auxiliary-task providers.
- sidebars.ts wires the new guide into the Guides section.
- scripts/release.py AUTHOR_MAP entries for TechPrototyper,
HangGlidersRule (noreply), and pein892 so the contributor-attribution
CI check does not reject the salvage.
The azure-foundry wizard now probes the endpoint before asking the user
to pick anything by hand:
1. URL path sniff — endpoints ending in /anthropic are Azure Foundry
Claude routes and skip to anthropic_messages.
2. GET <base>/models probe — if the endpoint returns an OpenAI-shaped
model list, we switch to chat_completions and prefill the picker
with the returned deployment/model IDs.
3. Anthropic Messages probe — fallback for endpoints that don't expose
/models but do speak the Anthropic Messages shape.
4. Manual fallback — private endpoints / custom routes still work;
the user picks API mode + types a deployment name.
Context length for the selected model is resolved through the existing
agent.model_metadata.get_model_context_length chain (models.dev,
provider metadata, hardcoded family fallbacks) and stored in
model.context_length when a non-default value is found.
Also refactors runtime_provider so Azure Foundry resolution is reused
between the explicit-credentials path and the default top-level path —
previously the /v1 strip for Anthropic-style Azure only ran when the
caller passed explicit_* args, which meant config-driven sessions
hit a double-/v1 URL.
New module hermes_cli/azure_detect.py with 19 unit tests covering:
- path sniff, model ID extraction, probe fallbacks
- HTTP error handling (URLError, HTTPError)
- context-length lookup passthrough
- DEFAULT_FALLBACK_CONTEXT rejection
New runtime tests cover:
- OpenAI-style Azure Foundry
- Anthropic-style Azure Foundry with /v1 stripping
- Missing base_url / API key raising AuthError
Rationale: Microsoft confirms there's no pure-API-key endpoint to list
Azure deployments (that requires ARM management auth). The v1 Azure
OpenAI endpoint does expose /models with the resource's available
model catalog, which is good enough for picker prefill in the common
case. Users on private/gated endpoints fall through to manual entry.
Azure OpenAI exposes an OpenAI-compatible endpoint at
`{resource}.openai.azure.com/openai/v1` that accepts the standard
`openai` Python client. Two issues prevented gpt-5.x models from working:
1. `_max_tokens_param()` only sent `max_completion_tokens` for
`api.openai.com` URLs. Azure also requires `max_completion_tokens`
for gpt-5.x models.
2. The `codex_responses` upgrade gate unconditionally upgraded gpt-5.x
to Responses API. Azure does NOT support the Responses API — it serves
gpt-5.x on the regular `/chat/completions` path, causing a 404.
Fix: add `_is_azure_openai_url()` that matches `openai.azure.com` URLs.
- `_max_tokens_param()` now returns `max_completion_tokens` for Azure.
- The `codex_responses` upgrade gate skips Azure so gpt-5.x stays on
`chat_completions` where Azure actually serves it.
- The fallback-provider api_mode picker also recognises Azure and stays
on chat_completions.
- Tests cover max_tokens routing, api_mode behaviour, and URL detection.
gpt-4.x models on Azure are unaffected (already used chat_completions +
max_tokens, which Azure accepts for those models).
Salvage of PR #10086 — rewritten against current main where the
codex_responses upgrade gate gained copilot-acp / explicit-api_mode
exclusions.
Azure OpenAI requires an `api-version` query parameter on every request.
When users include it in the base_url (e.g. `?api-version=2025-04-01-preview`),
the OpenAI SDK silently drops it during URL construction, causing 404 errors.
Extract query params from base_url and pass them via `default_query` so the
SDK appends them to every request. This is a generic solution that works for
any custom endpoint requiring query parameters, not just Azure.
No-op for URLs without query params — fully backward compatible.
Add support for Azure Foundry as a new inference provider. Azure Foundry
endpoints can use either OpenAI-style (/v1/chat/completions) or
Anthropic-style (/v1/messages) API formats.
Changes:
- Add azure-foundry to PROVIDER_REGISTRY (auth.py)
- Add azure-foundry overlay in HERMES_OVERLAYS (providers.py)
- Add empty model list for azure-foundry (models.py)
- Add _model_flow_azure_foundry() interactive setup (main.py)
- Add azure-foundry runtime resolution with api_mode support (runtime_provider.py)
- Add AZURE_FOUNDRY_API_KEY and AZURE_FOUNDRY_BASE_URL env vars (config.py)
Usage:
hermes model -> More providers -> Azure Foundry
The setup wizard prompts for:
- Endpoint URL
- API format (OpenAI or Anthropic-style)
- API key
- Model name
Configuration is saved to config.yaml (model.provider, model.base_url,
model.api_mode, model.default) and ~/.hermes/.env (AZURE_FOUNDRY_API_KEY).
Fixes#15779. Custom-provider per-model context_length (`custom_providers[].models.<id>.context_length`) is now honored across every resolution path, not just agent startup. Also adds 256K as the top probe tier and default fallback.
## What changed
New helper `hermes_cli.config.get_custom_provider_context_length()` — single source of truth for the per-model override lookup, with trailing-slash-insensitive base-url matching.
`agent.model_metadata.get_model_context_length()` gains an optional `custom_providers=` kwarg (step 0b — runs after explicit `config_context_length` but before every other probe).
Wired through five call sites that previously either duplicated the lookup or ignored it entirely:
- `run_agent.py` startup — refactored to use the new helper (dedups legacy inline loop, keeps invalid-value warning)
- `AIAgent.switch_model()` — re-reads custom_providers from live config on every /model switch
- `hermes_cli.model_switch.resolve_display_context_length()` — new `custom_providers=` kwarg
- `gateway/run.py` /model confirmation (picker callback + text path)
- `gateway/run.py` `_format_session_info` (/info)
## Context probe tiers
`CONTEXT_PROBE_TIERS = [256_000, 128_000, 64_000, 32_000, 16_000, 8_000]` — was `[128_000, ...]`. `DEFAULT_FALLBACK_CONTEXT` follows tier[0], so unknown models now default to 256K. The stale `128000` literal in the OpenRouter metadata-miss path is replaced with `DEFAULT_FALLBACK_CONTEXT` for consistency.
## Repro (from #15779)
```yaml
custom_providers:
- name: my-custom-endpoint
base_url: https://example.invalid/v1
model: gpt-5.5
models:
gpt-5.5:
context_length: 1050000
```
`/model gpt-5.5 --provider custom:my-custom-endpoint` → previously "Context: 128,000", now "Context: 1,050,000".
## Tests
- `tests/hermes_cli/test_custom_provider_context_length.py` — new file, 19 tests covering the helper, step-0b integration, and the 256K tier invariants
- `tests/hermes_cli/test_model_switch_context_display.py` — added regression tests for #15779 through the display resolver
- `tests/gateway/test_session_info.py` — updated default-fallback assertion (128K → 256K)
- `tests/agent/test_model_metadata.py` — updated tier assertions for the new top tier
task.cancel() can't preempt the run_in_executor thread running
run_conversation(), so we rely on agent.interrupt() to wake the loop.
Without a timeout, a slow/unresponsive interrupt blocks the HTTP
response indefinitely. Wrap the await in wait_for(shield(task), 5.0)
and log a warning on timeout.
Also tidy one extra space in the module docstring's /stop entry.
Add ability to interrupt a running agent via the runs API. Previously
/v1/runs could start a run and subscribe to events, but there was no
way to cancel it. The new endpoint stores agent and task references
during execution, calls agent.interrupt() to stop LLM calls, then
cancels the asyncio task.
Includes 15 tests covering start, events, and stop scenarios.
- resolveEditor() now returns argv (string[]) so EDITOR='code --wait'
and VISUAL='emacsclient -t' tokenize correctly into spawnSync's
separate command + args. Previously the whole string was passed as
argv[0] and would ENOENT.
- Skip the POSIX X_OK PATH walk on Windows; return ['notepad.exe']
there since fs.constants.X_OK is not meaningful and PATHEXT-based
resolution would need its own implementation.
- Surface openEditor() rejections via actions.sys instead of letting
them become unhandled promise rejections in the useInput callback.
- Hotkey docs/comment now say Cmd/Ctrl+G to match isAction()'s
platform-action-modifier behavior (Cmd on macOS, Ctrl elsewhere).
When the user interrupts a long-running task, prompt_toolkit tries to
flush stdout during emergency shutdown. If stdout is in a broken state
(redirected to /dev/null, pipe closed, terminal gone), the flush raises
`OSError: [Errno 5] Input/output error` which propagates unhandled and
crashes the CLI.
Two defense layers:
1. `_suppress_closed_loop_errors`: add `OSError` with `errno.EIO` to
the asyncio exception handler, matching the existing pattern for
`RuntimeError("Event loop is closed")` and `KeyError("is not
registered")`.
2. Outer `except (KeyError, OSError)` block: add `errno.EIO` check
before the existing string-match guards, silently suppressing the
error instead of printing a misleading stdin-related message.
Fixes#13710.
- editor.ts: collapse two private helpers into one flatMap-driven lookup,
keep `isExecutable` as the only named primitive, document the fallback
chain with prompt_toolkit parity
- editor.test.ts: hoist the `exe` helper out of `describe`, drop the
empty afterEach + dead mkdir branch, materialize expected paths before
the resolveEditor call so argument evaluation order doesn't bite
- useComposerState.openEditor: rmSync the mkdtemp dir (was leaking),
early-return on bad exit / empty buffer, run cleanup in finally
- useInputHandlers: cheap `ch.toLowerCase() === 'g'` guard before the
modifier check
- hermes-ink/screen.ts: pick up `npm run fix` import-sort cleanup so
lint passes
