DeepSeek's /anthropic endpoint requires thinking blocks to be replayed
in multi-turn conversations for reasoning continuity. The existing code
classified api.deepseek.com as a generic third-party endpoint and stripped
ALL thinking blocks, causing HTTP 400 from DeepSeek.
Fix: add _is_deepseek_anthropic_endpoint() detector (following the Kimi
precedent) and a dedicated branch that strips only signed Anthropic blocks
while preserving unsigned ones synthesised from reasoning_content.
This follows the exact same pattern as the Kimi exemption (issue #13848)
and does not change behavior for any other third-party endpoint (Azure,
Bedrock, MiniMax, etc.).
FixesNousResearch/hermes-agent#16748
The guard that drops Anthropic's `thinking` kwarg for Kimi endpoints was
matched on `https://api.kimi.com/coding` only. Users configuring a
custom Kimi-compatible gateway (or an official Moonshot host) with
`api_mode: anthropic_messages` fall through to the generic third-party
path, which strips thinking blocks AND still sends
`thinking={enabled,...}` → upstream rejects with HTTP 400
"reasoning_content is missing in assistant tool call message at index N"
on the next request after a tool call.
Replace `_is_kimi_coding_endpoint` callers (history replay + thinking
kwarg gate) with `_is_kimi_family_endpoint(base_url, model)` that also
matches the `api.kimi.com` / `moonshot.ai` / `moonshot.cn` hosts and
Kimi/Moonshot family model names (`kimi-`, `moonshot-`, `k1.`, `k2.`,
…) for custom / proxied endpoints. Keeps the UA-header check in
`build_anthropic_client` URL-only — the `claude-code/0.1.0` header is
an official-Kimi contract.
Plumbs optional `model` through `convert_messages_to_anthropic` so
the unsigned reasoning_content→thinking block synthesised for Kimi's
history validation survives the third-party signature-stripping pass
on custom hosts too.
Closes#17057.
The normalize_model_name() function unconditionally converted dots to
hyphens in all model names. This caused non-Anthropic models (e.g.
gpt-5.4) to be mangled to gpt-5-4 when routed through the Anthropic
adapter path, resulting in HTTP 404 from the backend.
Now only applies dot-to-hyphen conversion for models starting with
"claude-" or "anthropic/", which are the actual Anthropic model IDs.
Fixes NousResearch/hermes-agent#17171
Related: #7421, #13061, #16417
* perf(startup): lazy-import OpenAI, Anthropic, Firecrawl, account_usage
Four heavy SDK/module imports are now deferred off the hot startup path.
Net savings on cold module imports:
cli 1200 → 958 ms (-242)
run_agent 1220 → 901 ms (-319)
tools.web_tools 711 → 423 ms (-288)
agent.anthropic_adapter 230 → 15 ms (-215)
agent.auxiliary_client 253 → 68 ms (-185)
Four independent changes in one PR since they all use the same pattern
and share the same risk profile (heavy SDK import → lazy proxy or
function-local import):
1. tools/web_tools.py:
'from firecrawl import Firecrawl' moved into _get_firecrawl_client(),
which is only called when backend='firecrawl'. Users on Exa/Tavily/
Parallel pay zero firecrawl cost.
2. cli.py + gateway/run.py:
'from agent.account_usage import ...' moved into the /limits handlers.
account_usage transitively pulls the OpenAI SDK chain; only needed
when the user runs /limits.
3. agent/anthropic_adapter.py:
'try: import anthropic as _anthropic_sdk' replaced with a cached
'_get_anthropic_sdk()' accessor. The three usage sites
(build_anthropic_client, build_anthropic_bedrock_client,
read_claude_code_credentials_from_keychain) now resolve via the
accessor. All pre-existing test patches of
'agent.anthropic_adapter._anthropic_sdk' keep working because the
accessor respects any value already in module globals.
4. agent/auxiliary_client.py AND run_agent.py:
'from openai import OpenAI' replaced with an '_OpenAIProxy()' module-
level object that looks like the OpenAI class but imports the SDK on
first call/isinstance check. This preserves:
- 15+ in-module OpenAI(...) construction sites in auxiliary_client
and the single site in run_agent's _create_openai_client (Python's
function-scope name lookup finds the proxy, forwards the call);
- 'patch("agent.auxiliary_client.OpenAI", ...)' and
'patch("run_agent.OpenAI", ...)' test patterns used by 28+ test
files (patch replaces the module attribute as usual).
Tried two alternatives first:
- 'from openai._client import OpenAI' — doesn't skip openai/__init__.py
(the audit's hypothesis here was wrong).
- Module-level __getattr__ — works for external access but Python
function-scope name resolution skips __getattr__, so in-module
OpenAI(...) calls NameError.
Note: 'openai' still loads on 'import cli' because
cli.py -> neuter_async_httpx_del() -> openai._base_client, and
run_agent.py -> code_execution_tool.py (module-level
build_execute_code_schema) -> _load_config() -> 'from cli import
CLI_CONFIG'. Deferring those is a separate, larger change — out of scope
for this PR. The savings above all come from avoiding the openai/*,
anthropic/*, and firecrawl/* top-level type-tree imports on paths that
don't need them.
Verified:
- 302/302 tests in tests/agent/{test_anthropic_adapter,
test_bedrock_1m_context, test_minimax_provider, test_anthropic_keychain}
pass. Two pre-existing failures on main unchanged.
- 106/106 tests/agent/test_auxiliary_client.py pass (1 pre-existing fail).
- 97/97 tests/run_agent/test_create_openai_client_kwargs_isolation.py,
test_plugin_context_engine_init.py, test_invalid_context_length_warning.py,
test_api_max_retries_config.py,
tests/hermes_cli/test_gemini_provider.py, test_ollama_cloud_provider.py
pass (1 pre-existing fail).
- Live hermes chat smoke: 2 turns + /model switch + tool calls, zero
errors in the 57-line agent.log window.
- Module-level import of run_agent + auxiliary_client + anthropic_adapter
no longer pulls 'anthropic' or 'firecrawl' at all.
* fix(gateway): restore top-level account_usage import for test-patch surface
CI caught two failures in tests/gateway/test_usage_command.py that I
missed locally:
AttributeError: 'module' object at gateway.run has no attribute 'fetch_account_usage'
The test uses monkeypatch.setattr('gateway.run.fetch_account_usage', ...)
to inject a fake account-fetch call. Moving the import inside the
handler deleted that module-level attribute, breaking the patch surface.
Restoring the top-level import in gateway/run.py gives up the ~230 ms
gateway-boot savings from that one lazy, but:
1. the gateway is a long-running daemon — boot cost is paid once per
install, not per turn;
2. the other four lazy-imports (firecrawl, openai, anthropic, cli's
account_usage) remain in place and still account for the bulk of
the savings reported in the PR body;
3. preserving the patch surface keeps the established
'gateway.run.fetch_account_usage' monkeypatch pattern working
without touching tests.
Verified: tests/gateway/test_usage_command.py — 8 passed, 0 failed.
Full targeted sweep (2336 tests across agent/gateway/hermes_cli/run_agent):
2332 passed, 4 failed — all 4 pre-existing on main.
---------
Co-authored-by: teknium1 <teknium@users.noreply.github.com>
Mechanical cleanup across 43 files — removes 46 unused imports
(F401) and 14 unused local variables (F841) detected by
`ruff check --select F401,F841`. Net: -49 lines.
Also fixes a latent NameError in rl_cli.py where `get_hermes_home()`
was called at module line 32 before its import at line 65 — the
module never imported successfully on main. The ruff audit surfaced
this because it correctly saw the symbol as imported-but-unused
(the call happened before the import ran); the fix moves the import
to the top of the file alongside other stdlib imports.
One `# noqa: F401` kept in hermes_cli/status.py for `subprocess`:
tests monkeypatch `hermes_cli.status.subprocess` as a regression
guard that systemctl isn't called on Termux, so the name must
exist at module scope even though the module body doesn't reference
it. Docstring explains the reason.
Also fixes an invalid `# noqa:` directive in
gateway/platforms/discord.py:308 that lacked a rule code.
Co-authored-by: teknium1 <teknium@users.noreply.github.com>
Adds tools.schema_sanitizer.strip_nullable_unions as the single
implementation for collapsing anyOf/oneOf nullable unions. Both the
MCP input-schema normalizer and the Anthropic tool-schema guard now
delegate to it instead of re-implementing the same walk three times.
The global sanitizer also gains a final pass so any tool that slips
past the two earlier hooks (plugin tools, non-MCP custom tools with
Pydantic-shaped schemas) still gets safe input_schemas on Anthropic.
- tools/schema_sanitizer.py:
* New public strip_nullable_unions(schema, keep_nullable_hint=True).
* _sanitize_single_tool() calls it as a final pass (hint preserved
so coerce_tool_args can still map string "null" to None).
- tools/mcp_tool.py: _normalize_mcp_input_schema delegates.
- agent/anthropic_adapter.py: _normalize_tool_input_schema delegates
with keep_nullable_hint=False (Anthropic does not recognize nullable).
No behavioral change for the fix itself; tests (73/73 targeted +
E2E across MCP→sanitizer→Anthropic paths) pass.
* fix(anthropic): remove Claude Code fingerprinting from OAuth Messages API path
OAuth requests now identify as Hermes on the wire. Removed:
- "You are Claude Code, Anthropic's official CLI for Claude." system
prompt prepend
- Hermes Agent → Claude Code / Nous Research → Anthropic
system-prompt substitutions
- mcp_ tool-name prefix on outgoing tool schemas + message history
- Matching mcp_ strip on inbound tool_use blocks (strip_tool_prefix path
removed from AnthropicTransport.normalize_response, + all 5 call
sites in run_agent.py and auxiliary_client.py)
- user-agent: claude-cli/<v> (external, cli) and x-app: cli headers on
the Messages API client
Added:
- OAuth path strips context-1m-2025-08-07 — Anthropic rejects OAuth
requests carrying it with HTTP 400 'This authentication style is
incompatible with the long context beta header.'
Kept (auth plumbing, not identity spoofing):
- _is_oauth_token classifier and is_oauth flag threading
- Bearer vs x-api-key auth routing
- _OAUTH_ONLY_BETAS (claude-code-20250219, oauth-2025-04-20) — backend
requires these on the OAuth-gated Messages endpoint
- _OAUTH_CLIENT_ID (Claude Code's) — Anthropic doesn't issue OAuth
creds to third parties; this is the only way the login flow works
- claude-cli/<v> User-Agent on the OAuth token exchange + refresh
endpoints at platform.claude.com/v1/oauth/token — bare requests get
Cloudflare 1010 blocked
Verified live against api.anthropic.com with a fresh sk-ant-oat01-*
token:
- claude-haiku-4-5 simple message: HTTP 200, 'OK' response
- claude-haiku-4-5 tool call: HTTP 200, stop_reason=tool_use, tool
named 'terminal' (no mcp_ prefix) round-tripped correctly
- Outgoing wire: no user-agent, no x-app, real Hermes identity in
system prompt, real tool name in schema
Closes/supersedes #16820 (mcp_ PascalCase normalization patch — no longer
needed since the mcp_ round-trip is gone).
* fix(anthropic): resolve_anthropic_token() reads credential pool first
Close the gap where ~/.hermes/auth.json → credential_pool.anthropic
(where hermes login + dashboard PKCE flow write OAuth tokens) was not
in resolve_anthropic_token()'s source list.
Before: users who authed via hermes login got the token written into
the pool, but legacy fallback code paths (auxiliary_client, models
catalog fetch, explicit-runtime path) that call resolve_anthropic_token()
saw None and raised 'No Anthropic credentials found' — even though the
token was sitting in auth.json.
New priority 1: pool.select() with env-sourced entries skipped. Skipping
env:* entries preserves the existing env-var priority logic further
down the chain (static env OAuth → refreshable Claude Code upgrade via
_prefer_refreshable_claude_code_token).
Surfaced while writing the hermes-agent-dev skill playbook for
'finding a live OAuth token for an E2E test'.
---------
Co-authored-by: teknium1 <teknium@users.noreply.github.com>
Background macOS desktop control via cua-driver MCP — does NOT steal the
user's cursor or keyboard focus, works with any tool-capable model.
Replaces the Anthropic-native `computer_20251124` approach from the
abandoned #4562 with a generic OpenAI function-calling schema plus SOM
(set-of-mark) captures so Claude, GPT, Gemini, and open models can all
drive the desktop via numbered element indices.
- `tools/computer_use/` package — swappable ComputerUseBackend ABC +
CuaDriverBackend (stdio MCP client to trycua/cua's cua-driver binary).
- Universal `computer_use` tool with one schema for all providers.
Actions: capture (som/vision/ax), click, double_click, right_click,
middle_click, drag, scroll, type, key, wait, list_apps, focus_app.
- Multimodal tool-result envelope (`_multimodal=True`, OpenAI-style
`content: [text, image_url]` parts) that flows through
handle_function_call into the tool message. Anthropic adapter converts
into native `tool_result` image blocks; OpenAI-compatible providers
get the parts list directly.
- Image eviction in convert_messages_to_anthropic: only the 3 most
recent screenshots carry real image data; older ones become text
placeholders to cap per-turn token cost.
- Context compressor image pruning: old multimodal tool results have
their image parts stripped instead of being skipped.
- Image-aware token estimation: each image counts as a flat 1500 tokens
instead of its base64 char length (~1MB would have registered as
~250K tokens before).
- COMPUTER_USE_GUIDANCE system-prompt block — injected when the toolset
is active.
- Session DB persistence strips base64 from multimodal tool messages.
- Trajectory saver normalises multimodal messages to text-only.
- `hermes tools` post-setup installs cua-driver via the upstream script
and prints permission-grant instructions.
- CLI approval callback wired so destructive computer_use actions go
through the same prompt_toolkit approval dialog as terminal commands.
- Hard safety guards at the tool level: blocked type patterns
(curl|bash, sudo rm -rf, fork bomb), blocked key combos (empty trash,
force delete, lock screen, log out).
- Skill `apple/macos-computer-use/SKILL.md` — universal (model-agnostic)
workflow guide.
- Docs: `user-guide/features/computer-use.md` plus reference catalog
entries.
44 new tests in tests/tools/test_computer_use.py covering schema
shape (universal, not Anthropic-native), dispatch routing, safety
guards, multimodal envelope, Anthropic adapter conversion, screenshot
eviction, context compressor pruning, image-aware token estimation,
run_agent helpers, and universality guarantees.
469/469 pass across tests/tools/test_computer_use.py + the affected
agent/ test suites.
- `model_tools.py` provider-gating: the tool is available to every
provider. Providers without multi-part tool message support will see
text-only tool results (graceful degradation via `text_summary`).
- Anthropic server-side `clear_tool_uses_20250919` — deferred;
client-side eviction + compressor pruning cover the same cost ceiling
without a beta header.
- macOS only. cua-driver uses private SkyLight SPIs
(SLEventPostToPid, SLPSPostEventRecordTo,
_AXObserverAddNotificationAndCheckRemote) that can break on any macOS
update. Pin with HERMES_CUA_DRIVER_VERSION.
- Requires Accessibility + Screen Recording permissions — the post-setup
prints the Settings path.
Supersedes PR #4562 (pyautogui/Quartz foreground backend, Anthropic-
native schema). Credit @0xbyt4 for the original #3816 groundwork whose
context/eviction/token design is preserved here in generic form.
On AWS Bedrock (and Azure AI Foundry), Claude Opus 4.6/4.7 and Sonnet 4.6
are capped at 200K context unless the request carries the
`context-1m-2025-08-07` beta header. On native Anthropic (api.anthropic.com)
1M went GA so the header is a harmless no-op, but Bedrock/Azure still gate
it as beta as of 2026-04.
Hermes was advertising 1M in model_metadata.py (`claude-opus-4-7: 1000000`)
while silently sending a request without the beta — so Bedrock users saw
a 200K ceiling with no error message, and no config knob unblocked it.
Claude Code sends this header by default, which is why the same Bedrock
credentials worked there.
- Add `context-1m-2025-08-07` to `_COMMON_BETAS` (alongside interleaved
thinking and fine-grained tool streaming).
- Strip it in `_common_betas_for_base_url` for MiniMax bearer-auth
endpoints — they host their own models, not Claude, so Anthropic beta
headers are irrelevant and could risk rejection.
- Attach `_COMMON_BETAS` as `default_headers` on the AnthropicBedrock
client. Previously that constructor passed no betas at all, so native
Anthropic had the 1M unlock via default_headers but Bedrock didn't.
- Fast-mode per-request `extra_headers` already rebuilds from
`_common_betas_for_base_url`, so it picks up the 1M beta automatically.
Reported by user 'Rodmar' on Discord: Bedrock Opus 4.7 stuck at 200K while
same credentials worked in Claude Code.
The AIAgent.flush_memories pre-compression save, the gateway
_flush_memories_for_session, and everything feeding them are
obsolete now that the background memory/skill review handles
persistent memory extraction.
Problems with flush_memories:
- Pre-dates the background review loop. It was the only memory-save
path when introduced; the background review now fires every 10 user
turns on CLI and gateway alike, which is far more frequent than
compression or session reset ever triggered flush.
- Blocking and synchronous. Pre-compression flush ran on the live agent
before compression, blocking the user-visible response.
- Cache-breaking. Flush built a temporary conversation prefix
(system prompt + memory-only tool list) that diverged from the live
conversation's cached prefix, invalidating prompt caching. The
gateway variant spawned a fresh AIAgent with its own clean prompt
for each finalized session — still cache-breaking, just in a
different process.
- Redundant. Background review runs in the live conversation's
session context, gets the same content, writes to the same memory
store, and doesn't break the cache. Everything flush_memories
claimed to preserve is already covered.
What this removes:
- AIAgent.flush_memories() method (~248 LOC in run_agent.py)
- Pre-compression flush call in _compress_context
- flush_memories call sites in cli.py (/new + exit)
- GatewayRunner._flush_memories_for_session + _async_flush_memories
(and the 3 call sites: session expiry watcher, /new, /resume)
- 'flush_memories' entry from DEFAULT_CONFIG auxiliary tasks,
hermes tools UI task list, auxiliary_client docstrings
- _memory_flush_min_turns config + init
- #15631's headroom-deduction math in
_check_compression_model_feasibility (headroom was only needed
because flush dragged the full main-agent system prompt along;
the compression summariser sends a single user-role prompt so
new_threshold = aux_context is safe again)
- The dedicated test files and assertions that exercised
flush-specific paths
What this renames (with read-time backcompat on sessions.json):
- SessionEntry.memory_flushed -> SessionEntry.expiry_finalized.
The session-expiry watcher still uses the flag to avoid re-running
finalize/eviction on the same expired session; the new name
reflects what it now actually gates. from_dict() reads
'expiry_finalized' first, falls back to the legacy 'memory_flushed'
key so existing sessions.json files upgrade seamlessly.
Supersedes #15631 and #15638.
Tested: 383 targeted tests pass across run_agent/, agent/, cli/,
and gateway/ session-boundary suites. No behavior regressions —
background memory review continues to handle persistent memory
extraction on both CLI and gateway.
Bedrock model IDs use dots as namespace separators (anthropic.claude-opus-4-7,
us.anthropic.claude-sonnet-4-5-v1:0), not version separators.
normalize_model_name() was unconditionally converting all dots to hyphens,
producing invalid IDs that Bedrock rejects with HTTP 400/404.
This affected both the main agent loop (partially mitigated by
_anthropic_preserve_dots in run_agent.py) and all auxiliary client calls
(compression, session_search, vision, etc.) which go through
_AnthropicCompletionsAdapter and never pass preserve_dots=True.
Fix: add _is_bedrock_model_id() to detect Bedrock namespace prefixes
(anthropic., us., eu., ap., jp., global.) and skip dot-to-hyphen
conversion for these IDs regardless of the preserve_dots flag.
Bug 3 — Stale OAuth token not detected in 'hermes model':
- _model_flow_anthropic used 'has_creds = bool(existing_key)' which treats
any non-empty token (including expired OAuth tokens) as valid.
- Added existing_is_stale_oauth check: if the only credential is an OAuth
token (sk-ant- prefix) with no valid cc_creds fallback, mark it stale
and force the re-auth menu instead of silently accepting a broken token.
Bug 4 — macOS Keychain credentials never read:
- Claude Code >=2.1.114 migrated from ~/.claude/.credentials.json to the
macOS Keychain under service 'Claude Code-credentials'.
- Added _read_claude_code_credentials_from_keychain() using the 'security'
CLI tool; read_claude_code_credentials() now tries Keychain first then
falls back to JSON file.
- Non-Darwin platforms return None from Keychain read immediately.
Tests:
- tests/agent/test_anthropic_keychain.py: 11 cases covering Darwin-only
guard, security command failures, JSON parsing, fallback priority.
- tests/hermes_cli/test_anthropic_model_flow_stale_oauth.py: 8 cases
covering stale OAuth detection, API key passthrough, cc_creds fallback.
Refs: #12905
FixesNousResearch/hermes-agent#9813
Root cause: _is_oauth_token() only recognized sk-ant-* and eyJ* patterns,
but Claude Code OAuth tokens from CLAUDE_CODE_OAUTH_TOKEN use cc- prefix
Fix: Add cc- prefix detection so these tokens route through Bearer auth
NormalizedResponse and ToolCall now have backward-compat properties
so the agent loop can read them directly without the shim:
ToolCall: .type, .function (returns self), .call_id, .response_item_id
NormalizedResponse: .reasoning_content, .reasoning_details,
.codex_reasoning_items
This eliminates the 35-line shim and its 4 call sites in run_agent.py.
Also changes flush_memories guard from hasattr(response, 'choices')
to self.api_mode in ('chat_completions', 'bedrock_converse') so it
works with raw boto3 dicts too.
WS1 items 3+4 of Cycle 2 (#14418).
3-layer chain (transport → v2 → v1) was collapsed to 2-layer in PR 7.
This collapses the remaining 2-layer (transport → v1 → NR mapping in
transport) to 1-layer: v1 now returns NormalizedResponse directly.
Before: adapter returns (SimpleNamespace, finish_reason) tuple,
transport unpacks and maps to NormalizedResponse (22 lines).
After: adapter returns NormalizedResponse, transport is a
1-line passthrough.
Also updates ToolCall construction — adapter now creates ToolCall
dataclass directly instead of SimpleNamespace(id, type, function).
WS1 item 1 of Cycle 2 (#14418).
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.
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
Follow-up to the cherry-picked PR #13897 fix. Three issues found:
1. CRITICAL: The thinking block synthesised from reasoning_content was
immediately stripped by the third-party signature management code
(Kimi is classified as _is_third_party_anthropic_endpoint). Added a
Kimi-specific carve-out that preserves unsigned thinking blocks while
still stripping Anthropic-signed blocks Kimi can't validate.
2. Empty-string reasoning_content was silently dropped because the
truthiness check ('if reasoning_content and ...') evaluates to False
for ''. Changed to 'isinstance(reasoning_content, str)' so the
tier-3 fallback from _copy_reasoning_content_for_api (which injects
'' for Kimi tool-call messages with no reasoning) actually produces
a thinking block.
3. The thinking block was appended AFTER tool_use blocks. Anthropic
protocol requires thinking -> text -> tool_use ordering. Changed to
blocks.insert(0, ...) to prepend.
FixesNousResearch/hermes-agent#13848
Kimi's /coding endpoint speaks the Anthropic Messages protocol but has its
own thinking semantics: when thinking is enabled, Kimi validates message
history and requires every prior assistant tool-call message to carry
OpenAI-style reasoning_content.
The Anthropic path never populated that field, and
convert_messages_to_anthropic strips all Anthropic thinking blocks on
third-party endpoints — so the request failed with HTTP 400:
"thinking is enabled but reasoning_content is missing in assistant
tool call message at index N"
Now, when an assistant message contains tool_calls and a
reasoning_content string, we append a {"type": "thinking", ...} block
to the Anthropic content so Kimi can validate the history. This only
affects assistant messages with tool_calls + reasoning_content; plain
text assistant messages are unchanged.
Kimi's /coding endpoint speaks the Anthropic Messages protocol but has
its own thinking semantics: when thinking.enabled is sent, Kimi validates
the history and requires every prior assistant tool-call message to carry
OpenAI-style reasoning_content. The Anthropic path never populates that
field, and convert_messages_to_anthropic strips Anthropic thinking blocks
on third-party endpoints — so after one tool-calling turn the next request
fails with:
HTTP 400: thinking is enabled but reasoning_content is missing in
assistant tool call message at index N
Kimi on chat_completions handles thinking via extra_body in
ChatCompletionsTransport (#13503). On the Anthropic route, drop the
parameter entirely and let Kimi drive reasoning server-side.
build_anthropic_kwargs now gates the reasoning_config -> thinking block
on not _is_kimi_coding_endpoint(base_url).
Tests: 8 new parametric tests cover /coding, /coding/v1, /coding/anthropic,
/coding/ (trailing slash), explicit disabled, other third-party endpoints
still getting thinking (MiniMax), native Anthropic unaffected, and the
non-/coding Kimi root route.
- Add _is_kimi_coding_endpoint() to detect Kimi coding API
- Place Kimi check BEFORE _requires_bearer_auth to ensure User-Agent header is set
- Without this header, Kimi returns 403 on /coding/v1/messages
- Fixes kimi-2.5, kimi-for-coding, kimi-k2.6-code-preview all returning 403
Add agent/transports/types.py with three shared dataclasses:
- NormalizedResponse: content, tool_calls, finish_reason, reasoning, usage, provider_data
- ToolCall: id, name, arguments, provider_data (per-tool-call protocol metadata)
- Usage: prompt_tokens, completion_tokens, total_tokens, cached_tokens
Add normalize_anthropic_response_v2() to anthropic_adapter.py — wraps the
existing v1 function and maps its output to NormalizedResponse. One call site
in run_agent.py (the main normalize branch) uses v2 with a back-compat shim
to SimpleNamespace for downstream code.
No ABC, no registry, no streaming, no client lifecycle. Those land in PR 3
with the first concrete transport (AnthropicTransport).
46 new tests:
- test_types.py: dataclass construction, build_tool_call, map_finish_reason
- test_anthropic_normalize_v2.py: v1-vs-v2 regression tests (text, tools,
thinking, mixed, stop reasons, mcp prefix stripping, edge cases)
Part of the provider transport refactor (PR 2 of 9).
Follow-up on top of mvanhorn's cherry-picked commit. Original PR only
wired request_timeout_seconds into the explicit-creds OpenAI branch at
run_agent.py init; router-based implicit auth, native Anthropic, and the
fallback chain were still hardcoded to SDK defaults.
- agent/anthropic_adapter.py: build_anthropic_client() accepts an optional
timeout kwarg (default 900s preserved when unset/invalid).
- run_agent.py: resolve per-provider/per-model timeout once at init; apply
to Anthropic native init + post-refresh rebuild + stale/interrupt
rebuilds + switch_model + _restore_primary_runtime + the OpenAI
implicit-auth path + _try_activate_fallback (with immediate client
rebuild so the first fallback request carries the configured timeout).
- tests: cover anthropic adapter kwarg honoring; widen mock signatures
to accept the new timeout kwarg.
- docs/example: clarify that the knob now applies to every transport,
the fallback chain, and rebuilds after credential rotation.
Regression from #11161 (Claude Opus 4.7 migration, commit 0517ac3e).
The Opus 4.7 migration changed `ADAPTIVE_EFFORT_MAP["xhigh"]` from "max"
(the pre-migration alias) to "xhigh" to preserve the new 4.7 effort level
as distinct from max. This is correct for 4.7, but Opus/Sonnet 4.6 only
expose 4 levels (low/medium/high/max) — sending "xhigh" there now 400s:
BadRequestError [HTTP 400]: This model does not support effort
level 'xhigh'. Supported levels: high, low, max, medium.
Users who set reasoning_effort=xhigh as their default (xhigh is the
recommended default for coding/agentic on 4.7 per the Anthropic migration
guide) now 400 every request the moment they switch back to a 4.6 model
via `/model` or config. Verified live against the Anthropic API on
`anthropic==0.94.0`.
Fix: make the mapping model-aware. Add `_supports_xhigh_effort()`
predicate (matches 4-7/4.7 substrings, mirroring the existing
`_supports_adaptive_thinking` / `_forbids_sampling_params` pattern).
On pre-4.7 adaptive models, downgrade xhigh→max (the strongest effort
those models accept, restoring pre-migration behavior). On 4.7+, keep
xhigh as a distinct level.
Per Anthropic's migration guide, xhigh is 4.7-only:
https://platform.claude.com/docs/en/about-claude/models/migration-guide
> Opus 4.7 effort levels: max, xhigh (new), high, medium, low.
> Opus 4.6 effort levels: max, high, medium, low.
SDK typing confirms: `anthropic.types.OutputConfigParam.effort: Literal[
"low", "medium", "high", "max"]` (v0.94.0 not yet updated for xhigh).
## Test plan
Verified live on macOS 15.5 / anthropic==0.94.0:
claude-opus-4-6 + effort=xhigh → output_config.effort=max → 200 OK
claude-opus-4-7 + effort=xhigh → output_config.effort=xhigh → 200 OK
claude-opus-4-6 + effort=max → output_config.effort=max → 200 OK
claude-opus-4-7 + effort=max → output_config.effort=max → 200 OK
`tests/agent/test_anthropic_adapter.py` — 120 pass (replaced 1 bugged
test that asserted the broken behavior, added 1 for 4.7 preservation).
Full adapter suite: 120 passed in 1.05s.
Broader suite (agent + run_agent + cli/gateway reasoning): 2140 passed
(2 pre-existing failures on clean upstream/main, unrelated).
## Platforms
Tested on macOS 15.5. No platform-specific code paths touched.
Claude Opus 4.7 introduced several breaking API changes that the current
codebase partially handled but not completely. This patch finishes the
migration per the official migration guide at
https://platform.claude.com/docs/en/about-claude/models/migration-guideFixesNousResearch/hermes-agent#11137
Breaking-change coverage:
1. Adaptive thinking + output_config.effort — 4.7 is now recognized by
_supports_adaptive_thinking() (extends previous 4.6-only gate).
2. Sampling parameter stripping — 4.7 returns 400 for any non-default
temperature / top_p / top_k. build_anthropic_kwargs drops them as a
safety net; the OpenAI-protocol auxiliary path (_build_call_kwargs)
and AnthropicCompletionsAdapter.create() both early-exit before
setting temperature for 4.7+ models. This keeps flush_memories and
structured-JSON aux paths that hardcode temperature from 400ing
when the aux model is flipped to 4.7.
3. thinking.display = "summarized" — 4.7 defaults display to "omitted",
which silently hides reasoning text from Hermes's CLI activity feed
during long tool runs. Restoring "summarized" preserves 4.6 UX.
4. Effort level mapping — xhigh now maps to xhigh (was xhigh→max, which
silently over-efforted every coding/agentic request). max is now a
distinct ceiling per Anthropic's 5-level effort model.
5. New stop_reason values — refusal and model_context_window_exceeded
were silently collapsed to "stop" (end_turn) by the adapter's
stop_reason_map. Now mapped to "content_filter" and "length"
respectively, matching upstream finish-reason handling already in
bedrock_adapter.
6. Model catalogs — claude-opus-4-7 added to the Anthropic provider
list, anthropic/claude-opus-4.7 added at top of OpenRouter fallback
catalog (recommended), claude-opus-4-7 added to model_metadata
DEFAULT_CONTEXT_LENGTHS (1M, matching 4.6 per migration guide).
7. Prefill docstrings — run_agent.AIAgent and BatchRunner now document
that Anthropic Sonnet/Opus 4.6+ reject a trailing assistant-role
prefill (400).
8. Tests — 4 new tests in test_anthropic_adapter covering display
default, xhigh preservation, max on 4.7, refusal / context-overflow
stop_reason mapping, plus the sampling-param predicate. test_model_metadata
accepts 4.7 at 1M context.
Tested on macOS 15.5 (darwin). 119 tests pass in
tests/agent/test_anthropic_adapter.py, 1320 pass in tests/agent/.
Aligns MiniMax provider with official API documentation. Fixes 6 bugs:
transport mismatch (openai_chat -> anthropic_messages), credential leak
in switch_model(), prompt caching sent to non-Anthropic endpoints,
dot-to-hyphen model name corruption, trajectory compressor URL routing,
and stale doctor health check.
Also corrects context window (204,800), thinking support (manual mode),
max output (131,072), and model catalog (M2 family only on /anthropic).
Source: https://platform.minimax.io/docs/api-reference/text-anthropic-api
Co-authored-by: kshitijk4poor <kshitijk4poor@users.noreply.github.com>
_is_oauth_token() returned True for any key not starting with 'sk-ant-api',
which means MiniMax and Alibaba API keys were falsely treated as Anthropic
OAuth tokens. This triggered the Claude Code compatibility path:
- All tool names prefixed with mcp_ (e.g. mcp_terminal, mcp_web_search)
- System prompt injected with 'You are Claude Code' identity
- 'Hermes Agent' replaced with 'Claude Code' throughout
Fix: Make _is_oauth_token() positively identify Anthropic OAuth tokens by
their key format instead of using a broad catch-all:
- sk-ant-* (but not sk-ant-api-*) -> setup tokens, managed keys
- eyJ* -> JWTs from Anthropic OAuth flow
- Everything else -> False (MiniMax, Alibaba, etc.)
Reported by stefan171.
Automated dead code audit using vulture + coverage.py + ast-grep intersection,
confirmed by Opus deep verification pass. Every symbol verified to have zero
production callers (test imports excluded from reachability analysis).
Removes ~1,534 lines of dead production code across 46 files and ~1,382 lines
of stale test code. 3 entire files deleted (agent/builtin_memory_provider.py,
hermes_cli/checklist.py, tests/hermes_cli/test_setup_model_selection.py).
Co-authored-by: alt-glitch <balyan.sid@gmail.com>
Extends the /fast command to support Anthropic's Fast Mode beta in addition
to OpenAI Priority Processing. When enabled on Claude Opus 4.6, adds
speed:"fast" and the fast-mode-2026-02-01 beta header to API requests for
~2.5x faster output token throughput.
Changes:
- hermes_cli/models.py: Add _ANTHROPIC_FAST_MODE_MODELS registry,
model_supports_fast_mode() now recognizes Claude Opus 4.6,
resolve_fast_mode_overrides() returns {speed: fast} for Anthropic
vs {service_tier: priority} for OpenAI
- agent/anthropic_adapter.py: Add _FAST_MODE_BETA constant,
build_anthropic_kwargs() accepts fast_mode=True which injects
speed:fast + beta header via extra_headers (skipped for third-party
Anthropic-compatible endpoints like MiniMax)
- run_agent.py: Pass fast_mode to build_anthropic_kwargs in the
anthropic_messages path of _build_api_kwargs()
- cli.py: Update _handle_fast_command with provider-aware messaging
(shows 'Anthropic Fast Mode' vs 'Priority Processing')
- hermes_cli/commands.py: Update /fast description to mention both
providers
- tests: 13 new tests covering Anthropic model detection, override
resolution, CLI availability, routing, adapter kwargs, and
third-party endpoint safety
When the model mentions <think> as literal text in its response (e.g.
"(/think not producing <think> tags)"), the streaming display treated it
as a reasoning block opener and suppressed everything after it. The
response box would close with truncated content and no error — the API
response was complete but the display ate it.
Root cause: _stream_delta() matched <think> anywhere in the text stream
regardless of position. Real reasoning blocks always start at the
beginning of a line; mentions in prose appear mid-sentence.
Fix: track line position across streaming deltas with a
_stream_last_was_newline flag. Only enter reasoning suppression when
the tag appears at a block boundary (start of stream, after a newline,
or after only whitespace on the current line). Add a _flush_stream()
safety net that recovers buffered content if no closing tag is found
by end-of-stream.
Also fixes three related issues discovered during investigation:
- anthropic_adapter: _get_anthropic_max_output() now normalizes dots to
hyphens so 'claude-opus-4.6' matches the 'claude-opus-4-6' table key
(was returning 32K instead of 128K)
- run_agent: send explicit max_tokens for Claude models on Nous Portal,
same as OpenRouter — both proxy to Anthropic's API which requires it.
Without it the backend defaults to a low limit that truncates responses.
- run_agent: reset truncated_tool_call_retries after successful tool
execution so a single truncation doesn't poison the entire conversation.
MiniMax's Anthropic-compatible endpoints reject requests that include
the fine-grained-tool-streaming beta header — every tool-use message
triggers a connection error (~18s timeout). Regular chat works fine.
Add _common_betas_for_base_url() that filters out the tool-streaming
beta for Bearer-auth (MiniMax) endpoints while keeping all other betas.
All four client-construction branches now use the filtered list.
Based on #6528 by @HiddenPuppy.
Original cherry-picked from PR #6688 by kshitijk4poor.
Fixes#6510, fixes#6555.
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.
Two linked fixes for MiniMax Anthropic-compatible fallback:
1. Normalize httpx.URL to str before calling .rstrip() in auth/provider
detection helpers. Some client objects expose base_url as httpx.URL,
not str — crashed with AttributeError in _requires_bearer_auth() and
_is_third_party_anthropic_endpoint(). Also fixes _try_activate_fallback()
to use the already-stringified fb_base_url instead of raw httpx.URL.
2. Strip Anthropic-proprietary thinking block signatures when targeting
third-party Anthropic-compatible endpoints (MiniMax, Azure AI Foundry,
self-hosted proxies). These endpoints cannot validate Anthropic's
signatures and reject them with HTTP 400 'Invalid signature in
thinking block'. Now threads base_url through convert_messages_to_anthropic()
→ build_anthropic_kwargs() so signature management is endpoint-aware.
Based on PR #4945 by kshitijk4poor (rstrip fix).
Fixes#4944.
Anthropic signs thinking blocks against the full turn content. Any
upstream mutation (context compression, session truncation, orphan
stripping, message merging) invalidates the signature, causing HTTP 400
'Invalid signature in thinking block' — especially in long-lived
gateway sessions.
Strategy (following clawdbot/OpenClaw pattern):
1. Strip thinking/redacted_thinking from all assistant messages EXCEPT
the last one — preserves reasoning continuity on the current
tool-use chain while avoiding stale signature errors on older turns.
2. Downgrade unsigned thinking blocks to plain text — Anthropic can't
validate them, but the reasoning content is preserved.
3. Strip cache_control from thinking/redacted_thinking blocks to
prevent cache markers from interfering with signature validation.
4. Drop thinking blocks from the second message when merging
consecutive assistant messages (role alternation enforcement).
5. Error recovery: on HTTP 400 mentioning 'signature' and 'thinking',
strip all reasoning_details from the conversation and retry once.
This is the safety net for edge cases the proactive stripping
misses.
Addresses the issue reported in PR #6086 by @mingginwan while
preserving reasoning continuity (their PR stripped ALL thinking
blocks unconditionally).
Files changed:
- agent/anthropic_adapter.py: thinking block management in
convert_messages_to_anthropic (strip old turns, downgrade unsigned,
strip cache_control, merge-time strip)
- run_agent.py: one-shot signature error recovery in retry loop
- tests/test_anthropic_adapter.py: 10 new tests covering all cases
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.
Anthropic extended thinking blocks include an opaque 'signature' field
required for thinking chain continuity across multi-turn tool-use
conversations. Previously, normalize_anthropic_response() extracted
only the thinking text and set reasoning_details=None, discarding the
signature. On subsequent turns the API could not verify the chain.
Changes:
- _to_plain_data(): new recursive SDK-to-dict converter with depth cap
(20 levels) and path-based cycle detection for safety
- _extract_preserved_thinking_blocks(): rehydrates preserved thinking
blocks (including signature) from reasoning_details on assistant
messages, placing them before tool_use blocks as Anthropic requires
- normalize_anthropic_response(): stores full thinking blocks in
reasoning_details via _to_plain_data()
- _extract_reasoning(): adds 'thinking' key to the detail lookup chain
so Anthropic-format details are found alongside OpenRouter format
Salvaged from PR #4503 by @priveperfumes — focused on the thinking
block continuity fix only (cache strategy and other changes excluded).
* feat(auth): add same-provider credential pools and rotation UX
Add same-provider credential pooling so Hermes can rotate across
multiple credentials for a single provider, recover from exhausted
credentials without jumping providers immediately, and configure
that behavior directly in hermes setup.
- agent/credential_pool.py: persisted per-provider credential pools
- hermes auth add/list/remove/reset CLI commands
- 429/402/401 recovery with pool rotation in run_agent.py
- Setup wizard integration for pool strategy configuration
- Auto-seeding from env vars and existing OAuth state
Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
Salvaged from PR #2647
* fix(tests): prevent pool auto-seeding from host env in credential pool tests
Tests for non-pool Anthropic paths and auth remove were failing when
host env vars (ANTHROPIC_API_KEY) or file-backed OAuth credentials
were present. The pool auto-seeding picked these up, causing unexpected
pool entries in tests.
- Mock _select_pool_entry in auxiliary_client OAuth flag tests
- Clear Anthropic env vars and mock _seed_from_singletons in auth remove test
* feat(auth): add thread safety, least_used strategy, and request counting
- Add threading.Lock to CredentialPool for gateway thread safety
(concurrent requests from multiple gateway sessions could race on
pool state mutations without this)
- Add 'least_used' rotation strategy that selects the credential
with the lowest request_count, distributing load more evenly
- Add request_count field to PooledCredential for usage tracking
- Add mark_used() method to increment per-credential request counts
- Wrap select(), mark_exhausted_and_rotate(), and try_refresh_current()
with lock acquisition
- Add tests: least_used selection, mark_used counting, concurrent
thread safety (4 threads × 20 selects with no corruption)
* feat(auth): add interactive mode for bare 'hermes auth' command
When 'hermes auth' is called without a subcommand, it now launches an
interactive wizard that:
1. Shows full credential pool status across all providers
2. Offers a menu: add, remove, reset cooldowns, set strategy
3. For OAuth-capable providers (anthropic, nous, openai-codex), the
add flow explicitly asks 'API key or OAuth login?' — making it
clear that both auth types are supported for the same provider
4. Strategy picker shows all 4 options (fill_first, round_robin,
least_used, random) with the current selection marked
5. Remove flow shows entries with indices for easy selection
The subcommand paths (hermes auth add/list/remove/reset) still work
exactly as before for scripted/non-interactive use.
* fix(tests): update runtime_provider tests for config.yaml source of truth (#4165)
Tests were using OPENAI_BASE_URL env var which is no longer consulted
after #4165. Updated to use model config (provider, base_url, api_key)
which is the new single source of truth for custom endpoint URLs.
* feat(auth): support custom endpoint credential pools keyed by provider name
Custom OpenAI-compatible endpoints all share provider='custom', making
the provider-keyed pool useless. Now pools for custom endpoints are
keyed by 'custom:<normalized_name>' where the name comes from the
custom_providers config list (auto-generated from URL hostname).
- Pool key format: 'custom:together.ai', 'custom:local-(localhost:8080)'
- load_pool('custom:name') seeds from custom_providers api_key AND
model.api_key when base_url matches
- hermes auth add/list now shows custom endpoints alongside registry
providers
- _resolve_openrouter_runtime and _resolve_named_custom_runtime check
pool before falling back to single config key
- 6 new tests covering custom pool keying, seeding, and listing
* docs: add Excalidraw diagram of full credential pool flow
Comprehensive architecture diagram showing:
- Credential sources (env vars, auth.json OAuth, config.yaml, CLI)
- Pool storage and auto-seeding
- Runtime resolution paths (registry, custom, OpenRouter)
- Error recovery (429 retry-then-rotate, 402 immediate, 401 refresh)
- CLI management commands and strategy configuration
Open at: https://excalidraw.com/#json=2Ycqhqpi6f12E_3ITyiwh,c7u9jSt5BwrmiVzHGbm87g
* fix(tests): update setup wizard pool tests for unified select_provider_and_model flow
The setup wizard now delegates to select_provider_and_model() instead
of using its own prompt_choice-based provider picker. Tests needed:
- Mock select_provider_and_model as no-op (provider pre-written to config)
- Call _stub_tts BEFORE custom prompt_choice mock (it overwrites it)
- Pre-write model.provider to config so the pool step is reached
* docs: add comprehensive credential pool documentation
- New page: website/docs/user-guide/features/credential-pools.md
Full guide covering quick start, CLI commands, rotation strategies,
error recovery, custom endpoint pools, auto-discovery, thread safety,
architecture, and storage format.
- Updated fallback-providers.md to reference credential pools as the
first layer of resilience (same-provider rotation before cross-provider)
- Added hermes auth to CLI commands reference with usage examples
- Added credential_pool_strategies to configuration guide
* chore: remove excalidraw diagram from repo (external link only)
* refactor: simplify credential pool code — extract helpers, collapse extras, dedup patterns
- _load_config_safe(): replace 4 identical try/except/import blocks
- _iter_custom_providers(): shared generator for custom provider iteration
- PooledCredential.extra dict: collapse 11 round-trip-only fields
(token_type, scope, client_id, portal_base_url, obtained_at,
expires_in, agent_key_id, agent_key_expires_in, agent_key_reused,
agent_key_obtained_at, tls) into a single extra dict with
__getattr__ for backward-compatible access
- _available_entries(): shared exhaustion-check between select and peek
- Dedup anthropic OAuth seeding (hermes_pkce + claude_code identical)
- SimpleNamespace replaces class _Args boilerplate in auth_commands
- _try_resolve_from_custom_pool(): shared pool-check in runtime_provider
Net -17 lines. All 383 targeted tests pass.
---------
Co-authored-by: kshitijk4poor <82637225+kshitijk4poor@users.noreply.github.com>
Claude Code >=2.1.81 checks for a 'scopes' array containing 'user:inference'
in ~/.claude/.credentials.json before accepting stored OAuth tokens as valid.
When Hermes refreshes the token, it writes only accessToken, refreshToken, and
expiresAt — omitting the scopes field. This causes Claude Code to report
'loggedIn: false' and refuse to start, even though the token is valid.
This commit:
- Parses the 'scope' field from the OAuth refresh response
- Passes it to _write_claude_code_credentials() as a keyword argument
- Persists the scopes array in the claudeAiOauth credential store
- Preserves existing scopes when the refresh response omits the field
Tested against Claude Code v2.1.87 on Linux — auth status correctly reports
loggedIn: true and claude --print works after this fix.
Co-authored-by: Nick <git@flybynight.io>
* fix: treat non-sk-ant- prefixed keys (Azure AI Foundry) as regular API keys, not OAuth tokens
* fix: treat non-sk-ant- keys as regular API keys, not OAuth tokens
_is_oauth_token() returned True for any key not starting with
sk-ant-api, misclassifying Azure AI Foundry keys as OAuth tokens
and sending Bearer auth instead of x-api-key → 401 rejection.
Real Anthropic OAuth tokens all start with sk-ant-oat (confirmed
from live .credentials.json). Non-sk-ant- keys are third-party
provider keys that should use x-api-key.
Test fixtures updated to use realistic sk-ant-oat01- prefixed
tokens instead of fake strings.
Salvaged from PR #4075 by @HangGlidersRule.
---------
Co-authored-by: Clawdbot <clawdbot@openclaw.ai>
