Follow-up for #13862 — the post-init api_mode upgrade at __init__ (direct OpenAI /
gpt-5-requires-responses path) runs AFTER the eager transport warm. Clear the cache
so the stale chat_completions entry is evicted.
Cosmetic: correctness was already fine since _get_transport() keys by current
api_mode, but this avoids leaving unused cache state behind.
Consolidate 4 per-transport lazy singleton helpers (_get_anthropic_transport,
_get_codex_transport, _get_chat_completions_transport, _get_bedrock_transport)
into one generic _get_transport(api_mode) with a shared dict cache.
Collapse the 65-line main normalize block (3 api_mode branches, each with
its own SimpleNamespace shim) into 7 lines: one _get_transport() call +
one _nr_to_assistant_message() shared shim. The shim extracts provider_data
fields (codex_reasoning_items, reasoning_details, call_id, response_item_id)
into the SimpleNamespace shape downstream code expects.
Wire chat_completions and bedrock_converse normalize through their transports
for the first time — these were previously falling into the raw
response.choices[0].message else branch.
Remove 8 dead codex adapter imports that have zero callers after PRs 1-6.
Transport lifecycle improvements:
- Eagerly warm transport cache at __init__ (surfaces import errors early)
- Invalidate transport cache on api_mode change (switch_model, fallback
activation, fallback restore, transport recovery) — prevents stale
transport after mid-session provider switch
run_agent.py: -32 net lines (11,988 -> 11,956).
PR 7 of the provider transport refactor.
Follow-up to the /resume and /branch cleanup in the previous commit:
/new is a conversation-boundary operation too, so session-scoped
dangerous-command approvals and /yolo state must not survive it.
Adds a scoped unit test for _clear_session_boundary_security_state that
also covers the /new path (which calls the same helper).
On Windows, Path.open() defaults to the system ANSI code page (cp1252).
If the .env file contains UTF-8 characters, decoding fails with
'gbk codec can't decode byte 0x94'. Specify encoding='utf-8'
explicitly to ensure consistent behavior across platforms.
When a user manually sets fallback_model as a YAML list instead of a
dict, save_config_value() crashes with:
AttributeError: 'list' object has no attribute 'get'
at the fb.get('provider') call on hermes_cli/config.py.
The fix adds isinstance(fb, dict) so list-format values are treated as
unconfigured — the fallback_model comment block is appended to guide
correct usage — instead of crashing.
Fixes#4091
Co-authored-by: [AI-assisted — Claude Sonnet 4.6 via Milo/Hermes]
Commit 8254b820 ("--init for zombie reaping + sleep infinity for
idle-based lifetime") made the Docker terminal backend launch
sandbox containers with `sleep infinity` as the command, so the
lifetime is controlled by an external idle reaper instead of a
fixed timeout.
But `docker/entrypoint.sh` unconditionally wraps its args with
`hermes`:
exec hermes "$@"
Result: `hermes sleep infinity` → argparse rejects `sleep` as a
subcommand and the container exits immediately with code 2:
hermes: error: argument command: invalid choice: 'sleep'
(choose from chat, model, gateway, setup, ...)
Every sandbox container launched by the docker backend dies at
startup, breaking terminal/file tool execution end-to-end.
Fix: dispatch at the tail of the entrypoint. If the first arg is
an executable on PATH (sleep, bash, sh, etc.) run it raw; otherwise
preserve the legacy `hermes <subcommand>` wrapping behavior. Both
invocation styles below keep working:
docker run <image> -> hermes (interactive)
docker run <image> chat -q "hi" -> hermes chat -q "hi"
docker run <image> sleep infinity -> sleep infinity
docker run <image> bash -> bash
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
The Docker terminal backend runs containers with `--cap-drop ALL`
and re-adds only DAC_OVERRIDE, CHOWN, FOWNER. Since commit fee0e0d3
("run as non-root user, use virtualenv") the image entrypoint drops
from root to the `hermes` user via `gosu`, which requires CAP_SETUID
and CAP_SETGID. Without them every sandbox container exits
immediately with:
Dropping root privileges
error: failed switching to 'hermes': operation not permitted
Breaking every terminal/file tool invocation in `terminal.backend: docker`
mode.
Fix: add SETUID and SETGID to the cap-add list. The `no-new-privileges`
security-opt is kept, so gosu still cannot escalate back to root after
the one-way drop — the hardening posture is preserved.
Reproduction
------------
With any image whose ENTRYPOINT calls `gosu <user>`, the container
exits immediately under the pre-fix cap set. Post-fix, the drop
succeeds and the container proceeds normally.
docker run --rm \
--cap-drop ALL \
--cap-add DAC_OVERRIDE --cap-add CHOWN --cap-add FOWNER \
--security-opt no-new-privileges \
--entrypoint /usr/local/bin/gosu \
hermes-claude:latest hermes id
# -> error: failed switching to 'hermes': operation not permitted
# Same command with SETUID+SETGID added:
# -> uid=10000(hermes) gid=10000(hermes) groups=10000(hermes)
Tests
-----
Added `test_security_args_include_setuid_setgid_for_gosu_drop` that
asserts both caps are present and the overall hardening posture
(cap-drop ALL + no-new-privileges) is preserved.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Port from openclaw/openclaw#67318. Some open models (notably Gemma
variants served via OpenRouter) emit tool calls as XML blocks inside
assistant content instead of via the structured tool_calls field:
<function name="read_file"><parameter name="path">/tmp/x</parameter></function>
<tool_call>{"name":"x"}</tool_call>
<function_calls>[{...}]</function_calls>
Left unstripped, this raw XML leaked to gateway users (Discord, Telegram,
Matrix, Feishu, Signal, WhatsApp, etc.) and the CLI, since hermes-agent's
existing reasoning-tag stripper handled only <think>/<thinking>/<thought>
variants.
Extend _strip_think_blocks (run_agent.py) and _strip_reasoning_tags
(cli.py) to cover:
* <tool_call>, <tool_calls>, <tool_result>
* <function_call>, <function_calls>
* <function name="..."> ... </function> (Gemma-style)
The <function> variant is boundary-gated (only strips when the tag sits
at start-of-line or after sentence punctuation AND carries a name="..."
attribute) so prose mentions like 'Use <function> declarations in JS'
are preserved. Dangling <function name="..."> with no close is
intentionally left visible — matches OpenClaw's asymmetry so a truncated
streaming tail still reaches the user.
Tests: 9 new cases in TestStripThinkBlocks (run_agent) + 9 in new file
tests/run_agent/test_strip_reasoning_tags_cli.py. Covers Qwen-style
<tool_call>, Gemma-style <function name="...">, multi-line payloads,
prose preservation, stray close tags, dangling open tags, and mixed
reasoning+tool_call content.
Note: this port covers the post-streaming final-text path, which is what
gateway adapters and CLI display consume. Extending the per-delta stream
filter in gateway/stream_consumer.py to hide these tags live as they
stream is a separate follow-up; for now users may see raw XML briefly
during a stream before the final cleaned text replaces it.
Refs: openclaw/openclaw#67318
Feishu's open_id is app-scoped (same user gets different open_ids per
bot app), not a canonical identity. Functionally correct for single-bot
mode but semantically misleading.
- Add comprehensive Feishu identity model documentation to module docstring
- Prefer user_id (tenant-scoped) over open_id (app-scoped) in
_resolve_sender_profile when both are available
- Document bot_open_id usage for @mention matching
- Update user_id_alt comment in SessionSource to be platform-generic
Ref: closes analysis from PR #8388 (closed as over-scoped)
Port from openclaw/openclaw#66664. The build_anthropic_kwargs call site
used 'max_tokens or _get_anthropic_max_output(model)', which correctly
falls back when max_tokens is 0 or None (falsy) but lets negative ints
(-1, -500), fractional floats (0.5, 8192.7), NaN, and infinity leak
through to the Anthropic API. Anthropic rejects these with HTTP 400
('max_tokens: must be greater than or equal to 1'), turning a local
config error into a surprise mid-conversation failure.
Add two resolver helpers matching OpenClaw's:
_resolve_positive_anthropic_max_tokens — returns int(value) only if
value is a finite positive number; excludes bools, strings, NaN,
infinity, sub-one positives (floor to 0).
_resolve_anthropic_messages_max_tokens — prefers a positive requested
value, else falls back to the model's output ceiling; raises
ValueError only if no positive budget can be resolved.
The context-window clamp at the call site (max_tokens > context_length)
is preserved unchanged — it handles oversized values; the new resolver
handles non-positive values. These concerns are now cleanly separated.
Tests: 17 new cases covering positive/zero/negative ints, fractional
floats (both >1 and <1), NaN, infinity, booleans, strings, None, and
integration via build_anthropic_kwargs.
Refs: openclaw/openclaw#66664
_generate_summary() takes (turns_to_summarize, focus_topic) but the
summary model fallback path passed (messages, summary_budget) — where
'messages' is not even in scope, causing a NameError.
Fix the recursive call to pass the correct variables so the fallback
to the main model actually works when the summary model is unavailable.
Fixes: #10721
The Anthropic provider entry in PROVIDER_REGISTRY is the only standard
API-key provider missing a base_url_env_var. This causes the credential
pool to hardcode base_url to https://api.anthropic.com, ignoring
ANTHROPIC_BASE_URL from the environment.
When using a proxy (e.g. LiteLLM, custom gateway), subagent delegation
fails with 401 because:
1. _seed_from_env() creates pool entries with the hardcoded base_url
2. On error recovery, _swap_credential() overwrites the child agent's
proxy URL with the pool entry's api.anthropic.com
3. The proxy API key is sent to real Anthropic → authentication_error
Adding base_url_env_var="ANTHROPIC_BASE_URL" aligns Anthropic with the
20+ other providers that already have this field set (alibaba, gemini,
deepseek, xai, etc.).
LocalEnvironment._run_bash() spawned subprocess.Popen without a cwd
argument, so init_session()'s pwd -P ran in the gateway process's
startup directory and overwrote self.cwd. Pass cwd=self.cwd so the
initial snapshot captures the user-configured working directory.
Tested:
- pytest tests/ -q (255 env-related tests passed)
- Full suite: 13,537 passed; 70 pre-existing failures unrelated to local env
Running 'hermes profile create' inside the container creates wrappers at
/opt/data/.local/bin but that directory isn't on PATH by default.
Add ENV PATH so wrappers are discoverable without touching shell configs.
The container_config builder in terminal_tool.py was missing
docker_forward_env and docker_env keys, causing config.yaml's
docker_forward_env setting to be silently ignored. Environment
variables listed in docker_forward_env were never injected into
Docker containers.
This fix adds both keys to the container_config dict so they are
properly passed to _create_environment().
Follow-up on helix4u's PR #14211:
- Flip default to true: narrowing toolsets=['web','browser'] expresses
'I want these extras', not 'silently strip MCP'. Parent MCP tools
(registered at runtime) should survive narrowing by default.
- Drop _config_version bump (22->23); additive nested key under
delegation.* is handled by _deep_merge, no migration needed.
- Update tests to reflect new default behavior.
browser_cdp_tool.py registers before browser_tool.py (alphabetical
import order), so its stricter check_fn (requires CDP endpoint) becomes
the toolset-level check for all 11 browser tools. This causes
'hermes doctor' to report the entire browser toolset as unavailable
even when agent-browser is correctly installed.
Move browser_cdp to toolset='browser-cdp' so it is evaluated
independently. browser_navigate et al. only need agent-browser;
browser_cdp additionally requires a reachable CDP endpoint.
Mid-stream SSL alerts (bad_record_mac, tls_alert_internal_error, handshake
failures) previously fell through the classifier pipeline to the 'unknown'
bucket because:
- ssl.SSLError type names weren't in _TRANSPORT_ERROR_TYPES (the
isinstance(OSError) catch picks up some but not all SDK-wrapped forms)
- the message-pattern list had no SSL alert substrings
The 'unknown' bucket is still retryable, but: (a) logs tell the user
'unknown' instead of identifying the cause, (b) it bypasses the
transport-specific backoff/fallback logic, and (c) if the SSL error
happens on a large session with a generic 'connection closed' wrapper,
the existing disconnect-on-large-session heuristic would incorrectly
trigger context compression — expensive, and never fixes a transport
hiccup.
Changes:
- Add ssl.SSLError and its subclass type names to _TRANSPORT_ERROR_TYPES
- New _SSL_TRANSIENT_PATTERNS list (separate from _SERVER_DISCONNECT_PATTERNS
so SSL alerts route to timeout, not context_overflow+compress)
- New step 5 in the classifier pipeline: SSL pattern check runs BEFORE
the disconnect check to pre-empt the large-session-compress path
Patterns cover both space-separated ('ssl alert', 'bad record mac')
and underscore-separated ('ERR_SSL_SSL/TLS_ALERT_BAD_RECORD_MAC')
forms. This is load-bearing because OpenSSL 3.x changed the error-code
separator from underscore to slash (e.g. SSLV3_ALERT_BAD_RECORD_MAC →
SSL/TLS_ALERT_BAD_RECORD_MAC) and will likely churn again — matching on
stable alert reason substrings survives future format changes.
Tests (8 new):
- BAD_RECORD_MAC in Python ssl.c format
- OpenSSL 3.x underscore format
- TLSV1_ALERT_INTERNAL_ERROR
- ssl handshake failure
- [SSL: ...] prefix fallback
- Real ssl.SSLError instance
- REGRESSION GUARD: SSL on large session does NOT compress
- REGRESSION GUARD: plain disconnect on large session STILL compresses
os.walk() by default does not follow symlinks, causing skills
linked via symlinks to be invisible to the skill discovery system.
Add followlinks=True so that symlinked skill directories are scanned.
Port from cline/cline#10266.
When OpenAI-compatible proxies (OpenRouter, Vercel AI Gateway, Cline)
route Claude models, they sometimes surface the Anthropic-native cache
counters (`cache_read_input_tokens`, `cache_creation_input_tokens`) at
the top level of the `usage` object instead of nesting them inside
`prompt_tokens_details`. Our chat-completions branch of
`normalize_usage()` only read the nested `prompt_tokens_details` fields,
so those responses:
- reported `cache_write_tokens = 0` even when the model actually did a
prompt-cache write,
- reported only some of the cache-read tokens when the proxy exposed them
top-level only,
- overstated `input_tokens` by the missed cache-write amount, which in
turn made cost estimation and the status-bar cache-hit percentage wrong
for Claude traffic going through these gateways.
Now the chat-completions branch tries the OpenAI-standard
`prompt_tokens_details` first and falls back to the top-level
Anthropic-shape fields only if the nested values are absent/zero. The
Anthropic and Codex Responses branches are unchanged.
Regression guards added for three shapes: top-level write + nested read,
top-level-only, and both-present (nested wins).
