Follow-up to #12144. That PR standardized the kimi-k2.* temperature lock
against the Coding Plan endpoint (api.kimi.com/coding/v1) docs, where
non-thinking models require 0.6. Verified empirically against Moonshot
(April 2026) that the public chat endpoint (api.moonshot.ai/v1) has a
different contract for kimi-k2.5: it only accepts temperature=1, and rejects
0.6 with:
HTTP 400 "invalid temperature: only 1 is allowed for this model"
Users hit the public endpoint when KIMI_API_KEY is a legacy sk-* key (the
sk-kimi-* prefix routes to Coding Plan — see hermes_cli/auth.py). So for
Coding Plan subscribers the fix from #12144 is correct, but for public-API
users it reintroduces the exact 400 reported in #9125.
Reproduction on api.moonshot.ai/v1 + kimi-k2.5:
temperature=1.0 → 200 OK
temperature=0.6 → 400 "only 1 is allowed" ← #12144 default
temperature=None → 200 OK
Other kimi-k2.* models are unaffected empirically — turbo-preview accepts
0.6 and thinking-turbo accepts 1.0 on both endpoints — so only kimi-k2.5
diverges.
Fix: thread the client's actual base_url through _build_call_kwargs (the
parameter already existed but callers passed config-level resolved_base_url;
for auto-detected routes that was often empty). _fixed_temperature_for_model
now checks api.moonshot.ai first via an explicit _KIMI_PUBLIC_API_OVERRIDES
map, then falls back to the Coding Plan defaults. Tests parametrize over
endpoint + model to lock both contracts.
Closes#9125.
* fix(kimi): force fixed temperature on kimi-k2.* models (k2.5, thinking, turbo)
The prior override only matched the literal model name "kimi-for-coding",
but Moonshot's coding endpoint is hit with real model IDs such as
`kimi-k2.5`, `kimi-k2-turbo-preview`, `kimi-k2-thinking`, etc. Those
requests bypassed the override and kept the caller's temperature, so
Moonshot returns HTTP 400 "invalid temperature: only 0.6 is allowed for
this model" (or 1.0 for thinking variants).
Match the whole kimi-k2.* family:
* kimi-k2-thinking / kimi-k2-thinking-turbo -> 1.0 (thinking mode)
* all other kimi-k2.* -> 0.6 (non-thinking / instant mode)
Also accept an optional vendor prefix (e.g. `moonshotai/kimi-k2.5`) so
aggregator routings are covered.
* refactor(kimi): whitelist-match kimi coding models instead of prefix
Addresses review feedback on PR #12144.
- Replace `startswith("kimi-k2")` with explicit frozensets sourced from
Moonshot's kimi-for-coding model list. The prefix match would have also
clamped `kimi-k2-instruct` / `kimi-k2-instruct-0905`, which are the
separate non-coding K2 family with variable temperature (recommended 0.6
but not enforced — see huggingface.co/moonshotai/Kimi-K2-Instruct).
- Confirmed via platform.kimi.ai docs that all five coding models
(k2.5, k2-turbo-preview, k2-0905-preview, k2-thinking, k2-thinking-turbo)
share the fixed-temperature lock, so the preview-model mapping is no
longer an assumption.
- Drop the fragile `"thinking" in bare` substring test for a set lookup.
- Log a debug line on each override so operators can see when Hermes
silently rewrites temperature.
- Update class docstring. Extend the negative test to parametrize over
kimi-k2-instruct, Kimi-K2-Instruct-0905, and a hypothetical future
kimi-k2-experimental name — all must keep the caller's temperature.
First pass of test-suite reduction to address flaky CI and bloat.
Removed tests that fall into these change-detector patterns:
1. Source-grep tests (tests/gateway/test_feishu.py, test_email.py): tests
that call inspect.getsource() on production modules and grep for string
literals. Break on any refactor/rename even when behavior is correct.
2. Platform enum tautologies (every gateway/test_X.py): assertions like
`Platform.X.value == 'x'` duplicated across ~9 adapter test files.
3. Toolset/PLATFORM_HINTS/setup-wizard registry-presence checks: tests that
only verify a key exists in a dict. Data-layout tests, not behavior.
4. Argparse wiring tests (test_argparse_flag_propagation, test_subparser_routing
_fallback): tests that do parser.parse_args([...]) then assert args.field.
Tests Python's argparse, not our code.
5. Pure dispatch tests (test_plugins_cmd.TestPluginsCommandDispatch): patch
cmd_X, call plugins_command with matching action, assert mock called.
Tests the if/elif chain, not behavior.
6. Kwarg-to-mock verification (test_auxiliary_client ~45 tests,
test_web_tools_config, test_gemini_cloudcode, test_retaindb_plugin): tests
that mock the external API client, call our function, and assert exact
kwargs. Break on refactor even when behavior is preserved.
7. Schedule-internal "function-was-called" tests (acp/test_server scheduling
tests): tests that patch own helper method, then assert it was called.
Kept behavioral tests throughout: error paths (pytest.raises), security
tests (path traversal, SSRF, redaction), message alternation invariants,
provider API format conversion, streaming logic, memory contract, real
config load/merge tests.
Net reduction: 169 tests removed. 38 empty classes cleaned up.
Collected before: 12,522 tests
Collected after: 12,353 tests
Salvaged from PR #10643 by kshitijk4poor, updated for current main.
Root causes fixed:
1. Telegram xdist mock pollution — new tests/gateway/conftest.py with shared
mock that runs at collection time (prevents ChatType=None caching)
2. VIRTUAL_ENV env var leak — monkeypatch.delenv in _detect_venv_dir tests
3. Copilot base_url missing — add fallback in _resolve_runtime_from_pool_entry
4. Stale vision model assertion — zai now uses glm-5v-turbo
5. Reasoning item id intentionally stripped — assert 'id' not in (store=False)
6. Context length warning unreachable — pass base_url to AIAgent in test
7. Kimi provider label updated — 'Kimi / Kimi Coding Plan' matches models.py
8. Google Workspace calendar tests — rewritten for current production code,
properly mock subprocess on api_module, removed stale +agenda assertions
9. Credential pool auto-seeding — mock _select_pool_entry / _resolve_auto /
_import_codex_cli_tokens to prevent real credentials from leaking into tests
Production fixes:
- Add clear_session_context() to hermes_logging.py (fixes 48 teardown errors)
- Add clear_session() to tools/approval.py (fixes 9 setup errors)
- Add SyncError M_UNKNOWN_TOKEN check to Matrix _sync_loop (bug fix)
- Fall back to inline api_key in named custom providers when key_env
is absent (runtime_provider.py)
Test fixes:
- test_memory_user_id: use builtin+external provider pair, fix honcho
peer_name override test to match production behavior
- test_display_config: remove TestHelpers for non-existent functions
- test_auxiliary_client: fix OAuth tokens to match _is_oauth_token
patterns, replace get_vision_auxiliary_client with resolve_vision_provider_client
- test_cli_interrupt_subagent: add missing _execution_thread_id attr
- test_compress_focus: add model/provider/api_key/base_url/api_mode
to mock compressor
- test_auth_provider_gate: add autouse fixture to clean Anthropic env
vars that leak from CI secrets
- test_opencode_go_in_model_list: accept both 'built-in' and 'hermes'
source (models.dev API unavailable in CI)
- test_email: verify email Platform enum membership instead of source
inspection (build_channel_directory now uses dynamic enum loop)
- test_feishu: add bot_added/bot_deleted handler mocks to _Builder
- test_ws_auth_retry: add AsyncMock for sync_store.get_next_batch,
add _pending_megolm and _joined_rooms to Matrix adapter mocks
- test_restart_drain: monkeypatch-delete INVOCATION_ID (systemd sets
this in CI, changing the restart call signature)
- test_session_hygiene: add user_id to SessionSource
- test_session_env: use relative baseline for contextvar clear check
(pytest-xdist workers share context)
Remove the backward-compat code paths that read compression provider/model
settings from legacy config keys and env vars, which caused silent failures
when auto-detection resolved to incompatible backends.
What changed:
- Remove compression.summary_model, summary_provider, summary_base_url from
DEFAULT_CONFIG and cli.py defaults
- Remove backward-compat block in _resolve_task_provider_model() that read
from the legacy compression section
- Remove _get_auxiliary_provider() and _get_auxiliary_env_override() helper
functions (AUXILIARY_*/CONTEXT_* env var readers)
- Remove env var fallback chain for per-task overrides
- Update hermes config show to read from auxiliary.compression
- Add config migration (v16→17) that moves non-empty legacy values to
auxiliary.compression and strips the old keys
- Update example config and openclaw migration script
- Remove/update tests for deleted code paths
Compression model/provider is now configured exclusively via:
auxiliary.compression.provider / auxiliary.compression.model
Closes#8923
- Add openai/openai-codex -> openai mapping to PROVIDER_TO_MODELS_DEV
so context-length lookups use models.dev data instead of 128k fallback.
Fixes#8161.
- Set api_mode from custom_providers entry when switching via hermes model,
and clear stale api_mode when the entry has none. Also extract api_mode
in _named_custom_provider_map(). Fixes#8181.
- Convert OpenAI image_url content blocks to Anthropic image blocks when
the endpoint is Anthropic-compatible (MiniMax, MiniMax-CN, or any URL
containing /anthropic). Fixes#8147.
Four fixes to auxiliary_client.py:
1. Respect explicit provider as hard constraint (#7559)
When auxiliary.{task}.provider is explicitly set (not 'auto'),
connection/payment errors no longer silently fallback to cloud
providers. Local-only users (Ollama, vLLM) will no longer get
unexpected OpenRouter billing from auxiliary tasks.
2. Eliminate model='default' sentinel (#7512)
_resolve_api_key_provider() no longer sends literal 'default' as
model name to APIs. Providers without a known aux model in
_API_KEY_PROVIDER_AUX_MODELS are skipped instead of producing
model_not_supported errors.
3. Add payment/connection fallback to async_call_llm (#7512)
async_call_llm now mirrors sync call_llm's fallback logic for
payment (402) and connection errors. Previously, async consumers
(session_search, web_tools, vision) got hard failures with no
recovery. Also fixes hardcoded 'openrouter' fallback to use the
full auto-detection chain.
4. Use accurate error reason in fallback logs (#7512)
_try_payment_fallback() now accepts a reason parameter and uses
it in log messages. Connection timeouts are no longer misleadingly
logged as 'payment error'.
Closes#7559Closes#7512
The auxiliary client always calls client.chat.completions.create(),
ignoring the api_mode config flag. This breaks codex-family models
(e.g. gpt-5.3-codex) on direct OpenAI API keys, which need the
/v1/responses endpoint.
Changes:
- Expand _resolve_task_provider_model to return api_mode (5-tuple)
- Read api_mode from auxiliary.{task}.api_mode config and env vars
(AUXILIARY_{TASK}_API_MODE)
- Pass api_mode through _get_cached_client to resolve_provider_client
- Add _needs_codex_wrap/_wrap_if_needed helpers that wrap plain OpenAI
clients in CodexAuxiliaryClient when api_mode=codex_responses or
when auto-detection finds api.openai.com + codex model pattern
- Apply wrapping at all custom endpoint, named custom provider, and
API-key provider return paths
- Update test mocks for the new 5-tuple return format
Users can now set:
auxiliary:
compression:
model: gpt-5.3-codex
base_url: https://api.openai.com/v1
api_mode: codex_responses
Closes#6800
GPT-5+ models (except gpt-5-mini) are only accessible via the Responses
API on Copilot. When these models were configured as the compression
summary_model (or any auxiliary task), the plain OpenAI client sent them
to /chat/completions which returned a 400 error:
model "gpt-5.4-mini" is not accessible via the /chat/completions endpoint
resolve_provider_client() now checks _should_use_copilot_responses_api()
for the copilot provider and wraps the client in CodexAuxiliaryClient
when needed, routing calls through responses.stream() transparently.
Adds tests for both the wrapping (gpt-5.4-mini) and non-wrapping
(gpt-4.1-mini) paths.
_resolve_api_key_provider() now checks is_provider_explicitly_configured
before calling _try_anthropic(). Previously, any auxiliary fallback
(e.g. when kimi-coding key was invalid) would silently discover and use
Claude Code OAuth tokens — consuming the user's Claude Max subscription
without their knowledge.
This is the auxiliary-client counterpart of the setup-wizard gate in
PR #4210.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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>
Fixes 9 test failures on current main, incorporating ideas from PR stack
#6219-#6222 by xinbenlv with corrections:
- model_metadata: sync HF context length key casing
(minimaxai/minimax-m2.5 → MiniMaxAI/MiniMax-M2.5)
- cli.py: route quick command error output through self.console
instead of creating a new ChatConsole() instance
- docker.py: explicit docker_forward_env entries now bypass the
Hermes secret blocklist (intentional opt-in wins over generic filter)
- auxiliary_client: revert _read_main_provider() to simple
provider.strip().lower() — the _normalize_aux_provider() call
introduced in 5c03f2e7 stripped the custom: prefix, breaking
named custom provider resolution
- auxiliary_client: flip vision auto-detection order to
active provider → OpenRouter → Nous → stop (was OR → Nous → active)
- test: update vision priority test to match new order
Based on PR #6219-#6222 by xinbenlv.
Simplify the vision auto-detection chain from 5 backends (openrouter,
nous, codex, anthropic, custom) down to 3:
1. OpenRouter (known vision-capable default model)
2. Nous Portal (known vision-capable default model)
3. Active provider + model (whatever the user is running)
4. Stop
This is simpler and more predictable. The active provider step uses
resolve_provider_client() which handles all provider types including
named custom providers (from #5978).
Removed the complex preferred-provider promotion logic and API-level
fallback — the chain is short enough that it doesn't need them.
Based on PR #5376 by Mibay. Closes#5366.
Salvaged fixes from community PRs:
- fix(model_switch): _read_auth_store → _load_auth_store + fix auth store
key lookup (was checking top-level dict instead of store['providers']).
OAuth providers now correctly detected in /model picker.
Cherry-picked from PR #5911 by Xule Lin (linxule).
- fix(ollama): pass num_ctx to override 2048 default context window.
Ollama defaults to 2048 context regardless of model capabilities. Now
auto-detects from /api/show metadata and injects num_ctx into every
request. Config override via model.ollama_num_ctx. Fixes#2708.
Cherry-picked from PR #5929 by kshitij (kshitijk4poor).
- fix(aux): normalize provider aliases for vision/auxiliary routing.
Adds _normalize_aux_provider() with 17 aliases (google→gemini,
claude→anthropic, glm→zai, etc). Fixes vision routing failure when
provider is set to 'google' instead of 'gemini'.
Cherry-picked from PR #5793 by e11i (Elizabeth1979).
- fix(aux): rewrite MiniMax /anthropic base URLs to /v1 for OpenAI SDK.
MiniMax's inference_base_url ends in /anthropic (Anthropic Messages API),
but auxiliary client uses OpenAI SDK which appends /chat/completions →
404 at /anthropic/chat/completions. Generic _to_openai_base_url() helper
rewrites terminal /anthropic to /v1 for OpenAI-compatible endpoint.
Inspired by PR #5786 by Lempkey.
Added debug logging to silent exception blocks across all fixes.
Co-authored-by: Hermes Agent <hermes@nousresearch.com>
When a user runs out of OpenRouter credits and switches to Codex (or any
other provider), auxiliary tasks (compression, vision, web_extract) would
still try OpenRouter first and fail with 402. Two fixes:
1. Payment fallback in call_llm(): When a resolved provider returns HTTP 402
or a credit-related error, automatically retry with the next available
provider in the auto-detection chain. Skips the depleted provider and
tries Nous → Custom → Codex → API-key providers.
2. Remove hardcoded OpenRouter fallback: The old code fell back specifically
to OpenRouter when auto/custom resolution returned no client. Now falls
back to the full auto-detection chain, which handles any available
provider — not just OpenRouter.
Also extracts _get_provider_chain() as a shared function (replaces inline
tuple in _resolve_auto and the new fallback), built at call time so test
patches on _try_* functions remain visible.
Adds 16 tests covering _is_payment_error(), _get_provider_chain(),
_try_payment_fallback(), and call_llm() integration with 402 retry.
Three root causes addressed:
1. AIAgent no longer defaults base_url to OpenRouter (9 tests)
Tests that assert OpenRouter-specific behavior (prompt caching,
reasoning extra_body, provider preferences) need explicit base_url
and model set on the agent. Updated test_run_agent.py and
test_provider_parity.py.
2. Credential pool auto-seeding from host env (2 tests)
test_auxiliary_client.py tests for Anthropic OAuth and custom
endpoint fallback were not mocking _select_pool_entry, so the
host's credential pool interfered. Added pool + codex mocks.
3. sys.modules corruption cascade (major - ~250 tests)
test_managed_modal_environment.py replaced sys.modules entries
(tools, hermes_cli, agent packages) with SimpleNamespace stubs
but had NO cleanup fixture. Every subsequent test in the process
saw corrupted imports: 'cannot import get_config_path from
<unknown module name>' and 'module tools has no attribute
environments'. Added _restore_tool_and_agent_modules autouse
fixture matching the pattern in test_managed_browserbase_and_modal.py.
This was also the root cause of CI failures (104 failed on main).
* 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>
OPENAI_BASE_URL was written to .env AND config.yaml, creating a dual-source
confusion. Users (especially Docker) would see the URL in .env and assume
that's where all config lives, then wonder why LLM_MODEL in .env didn't work.
Changes:
- Remove all 27 save_env_value("OPENAI_BASE_URL", ...) calls across main.py,
setup.py, and tools_config.py
- Remove OPENAI_BASE_URL env var reading from runtime_provider.py, cli.py,
models.py, and gateway/run.py
- Remove LLM_MODEL/HERMES_MODEL env var reading from gateway/run.py and
auxiliary_client.py — config.yaml model.default is authoritative
- Vision base URL now saved to config.yaml auxiliary.vision.base_url
(both setup wizard and tools_config paths)
- Tests updated to set config values instead of env vars
Convention enforced: .env is for SECRETS only (API keys). All other
configuration (model names, base URLs, provider selection) lives
exclusively in config.yaml.
* 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>
Local inference servers (Ollama, llama.cpp, vLLM, LM Studio) don't
require API keys, but the auxiliary client's _resolve_custom_runtime()
rejected endpoints with empty keys — causing the auto-detection chain
to skip the user's local server entirely. This broke compression,
summarization, and memory flush for users running local models without
an OpenRouter/cloud API key.
The main CLI already had this fix (PR #2556, 'no-key-required'
placeholder), but the auxiliary client's resolution path was missed.
Two fixes:
- _resolve_custom_runtime(): use 'no-key-required' placeholder instead
of returning None when base_url is present but key is empty
- resolve_provider_client() custom branch: same placeholder fallback
for explicit_base_url without explicit_api_key
Updates 2 tests that expected the old (broken) behavior.
Nous Portal now passes through OpenRouter model names and routes from
there. Update the static fallback model list and auxiliary client default
to use OpenRouter-format slugs (provider/model) instead of bare names.
- _PROVIDER_MODELS['nous']: full OpenRouter catalog
- _NOUS_MODEL: google/gemini-3-flash-preview (was gemini-3-flash)
- Updated 4 test assertions for the new default model name
Remove run_hermes_oauth_login(), refresh_hermes_oauth_token(),
read_hermes_oauth_credentials(), _save_hermes_oauth_credentials(),
_generate_pkce(), and associated constants/credential file path.
This code was added in 63e88326 but never wired into any user-facing
flow (setup wizard, hermes model, or any CLI command). Neither
clawdbot/OpenClaw nor opencode implement PKCE for Anthropic — both
use setup-token or API keys. Dead code that was never tested in
production.
Also removes the credential resolution step that checked
~/.hermes/.anthropic_oauth.json (step 3 in resolve_anthropic_token),
renumbering remaining steps.
Two bugs in the auxiliary provider auto-detection chain:
1. Expired Codex JWT blocks the auto chain: _read_codex_access_token()
returned any stored token without checking expiry, preventing fallback
to working providers. Now decodes JWT exp claim and returns None for
expired tokens.
2. Auxiliary Anthropic client missing OAuth identity transforms:
_AnthropicCompletionsAdapter always called build_anthropic_kwargs with
is_oauth=False, causing 400 errors for OAuth tokens. Now detects OAuth
tokens via _is_oauth_token() and propagates the flag through the
adapter chain.
Cherry-picked from PR #2378 by 0xbyt4. Fixed test_api_key_no_oauth_flag
to mock resolve_anthropic_token directly (env var alone was insufficient).
Add first-class GitHub Copilot and Copilot ACP provider support across
model selection, runtime provider resolution, CLI sessions, delegated
subagents, cron jobs, and the Telegram gateway.
This also normalizes Copilot model catalogs and API modes, introduces a
Copilot ACP OpenAI-compatible shim, and fixes service-mode auth by
resolving Homebrew-installed gh binaries under launchd.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- Add summary_base_url config option to compression block for custom
OpenAI-compatible endpoints (e.g. zai, DeepSeek, Ollama)
- Remove compression env var bridges from cli.py and gateway/run.py
(CONTEXT_COMPRESSION_* env vars no longer set from config)
- Switch run_agent.py to read compression config directly from
config.yaml instead of env vars
- Fix backwards-compat block in _resolve_task_provider_model to also
fire when auxiliary.compression.provider is 'auto' (DEFAULT_CONFIG
sets this, which was silently preventing the compression section's
summary_* keys from being read)
- Add test for summary_base_url config-to-client flow
- Update docs to show compression as config.yaml-only
Closes#1591
Based on PR #1702 by @uzaylisak
Add base_url/api_key overrides for auxiliary tasks and delegation so users can
route those flows straight to a custom OpenAI-compatible endpoint without
having to rely on provider=main or named custom providers.
Also clear gateway session env vars in test isolation so the full suite stays
deterministic when run from a messaging-backed agent session.
* fix: prevent model/provider mismatch when switching providers during active gateway
When _update_config_for_provider() writes the new provider and base_url
to config.yaml, the gateway (which re-reads config per-message) can pick
up the change before model selection completes. This causes the old model
name (e.g. 'anthropic/claude-opus-4.6') to be sent to the new provider's
API (e.g. MiniMax), which fails.
Changes:
- _update_config_for_provider() now accepts an optional default_model
parameter. When provided and the current model.default is empty or
uses OpenRouter format (contains '/'), it sets a safe default model
for the new provider.
- All setup.py callers for direct-API providers (zai, kimi, minimax,
minimax-cn, anthropic) now pass a provider-appropriate default model.
- _setup_provider_model_selection() now validates the 'Keep current'
choice: if the current model uses OpenRouter format and wouldn't work
with the new provider, it warns and switches to the provider's first
default model instead of silently keeping the incompatible name.
Reported by a user on Home Assistant whose gateway started sending
'anthropic/claude-opus-4.6' to MiniMax's API after running hermes setup.
* fix: auxiliary client uses main model for custom/local endpoints instead of gpt-4o-mini
When a user runs a local server (e.g. Qwen3.5-9B via OPENAI_BASE_URL),
the auxiliary client (context compression, vision, session search) would
send requests for 'gpt-4o-mini' or 'google/gemini-3-flash-preview' to
the local server, which only serves one model — causing 404 errors
mid-task.
Changes:
- _try_custom_endpoint() now reads the user's configured main model via
_read_main_model() (checks OPENAI_MODEL → HERMES_MODEL → LLM_MODEL →
config.yaml model.default) instead of hardcoding 'gpt-4o-mini'.
- resolve_provider_client() auto mode now detects when an OpenRouter-
formatted model override (containing '/') would be sent to a non-
OpenRouter provider (like a local server) and drops it in favor of
the provider's default model.
- Test isolation fixes: properly clear env vars in 'nothing available'
tests to prevent host environment leakage.
Vision auto-mode previously only tried OpenRouter, Nous, and Codex
for multimodal — deliberately skipping custom endpoints with the
assumption they 'may not handle vision input.' This caused silent
failures for users running local multimodal models (Qwen-VL, LLaVA,
Pixtral, etc.) without any cloud API keys.
Now custom endpoints are tried as a last resort in auto mode. If the
model doesn't support vision, the API call fails gracefully — but
users with local vision models no longer need to manually set
auxiliary.vision.provider: main in config.yaml.
Reported by @Spadav and @kotyKD.
The 'openai' provider was redundant — using OPENAI_BASE_URL +
OPENAI_API_KEY with provider: 'main' already covers direct OpenAI API.
Provider options are now: auto, openrouter, nous, codex, main.
- Removed _try_openai(), _OPENAI_AUX_MODEL, _OPENAI_BASE_URL
- Replaced openai tests with codex provider tests
- Updated all docs to remove 'openai' option and clarify 'main'
- 'main' description now explicitly mentions it works with OpenAI API,
local models, and any OpenAI-compatible endpoint
Tests: 2467 passed.
The Codex Responses API (chatgpt.com/backend-api/codex) supports
vision via gpt-5.3-codex. This was verified with real API calls
using image analysis.
Changes to _CodexCompletionsAdapter:
- Added _convert_content_for_responses() to translate chat.completions
multimodal format to Responses API format:
- {type: 'text'} → {type: 'input_text'}
- {type: 'image_url', image_url: {url: '...'}} → {type: 'input_image', image_url: '...'}
- Fixed: removed 'stream' from resp_kwargs (responses.stream() handles it)
- Fixed: removed max_output_tokens and temperature (Codex endpoint rejects them)
Provider changes:
- Added 'codex' as explicit auxiliary provider option
- Vision auto-fallback now includes Codex (OpenRouter → Nous → Codex)
since gpt-5.3-codex supports multimodal input
- Updated docs with Codex OAuth examples
Tested with real Codex OAuth token + ~/.hermes/image2.png — confirmed
working end-to-end through the full adapter pipeline.
Tests: 2459 passed.
Users can now set provider: "openai" for auxiliary tasks (vision, web
extract, compression) to use OpenAI's API directly with their
OPENAI_API_KEY. This hits api.openai.com/v1 with gpt-4o-mini as the
default model — supports vision since GPT-4o handles image input.
Provider options are now: auto, openrouter, nous, openai, main.
Changes:
- agent/auxiliary_client.py: added _try_openai(), "openai" case in
_resolve_forced_provider(), updated auxiliary_max_tokens_param()
to use max_completion_tokens for OpenAI
- Updated docs: cli-config.yaml.example, AGENTS.md, and user-facing
configuration.md with Common Setups section showing OpenAI,
OpenRouter, and local model examples
- 3 new tests for OpenAI provider resolution
Tests: 2459 passed (was 2429).
