Qwen3.8 Max is live on both OpenRouter and the Nous portal
(qwen/qwen3.8-max, 1M context, 131K max output). Per the
newest-max-replaces-last-max convention, it takes qwen3.7-max's slot
in both curated lists.
- hermes_cli/models.py: OPENROUTER_MODELS + _PROVIDER_MODELS[nous]
swap qwen/qwen3.7-max -> qwen/qwen3.8-max
- agent/model_metadata.py: DEFAULT_CONTEXT_LENGTHS entry for
qwen3.8-max at 1,000,000 (verified against OpenRouter live
metadata and Nous /v1/models 2026-08-03)
- tests/test_empty_model_fallback.py: swap incidental catalog fixture
to the surviving slug
- website/static/api/model-catalog.json: regenerated
Pricing snapshot skipped: both routes bill via official_models_api
(live pricing), verified with resolve_billing_route. Reasoning
timeout floor already covered by the qwen3 prefix (180s).
Salvage of #71282 (Fixes#71281): a routable-but-dead endpoint (corp
LAN address while off-VPN) blackholes TCP SYNs, so every probe in the
model-metadata waterfall waits out its full connect timeout — 20+
seconds of stall per startup across detect_local_server_type,
fetch_endpoint_model_metadata, and the per-model probes.
A module-level blackhole cache keyed on host:port is populated when
any probe observes a ConnectTimeout (httpx or requests; read timeouts
deliberately excluded — an accepted connection is not a blackhole) and
consulted at the top of each guarded function. 30s TTL: long enough to
collapse one startup burst, short enough that VPN recovery is picked
up without a restart. Guard ordering: blackhole check -> disk L2 ->
HTTP waterfall, and a blackholed leg aborts the remaining legs instead
of letting each stall in turn.
Squash of the PR's two real commits (the branch's merge commits made
it un-rebase-merge-able; content verified identical via merge-tree).
CI slice 3/7 failures: run_conversation tests pass MagicMock base_urls
through the metadata probe path; re.sub raised TypeError where the old
code let non-strings flow through. Preserve that contract.
fetch_endpoint_model_metadata's generic (non-LM-Studio) /models fetch and
its llama.cpp /v1/props context-length follow-up built request URLs
straight from the unrewritten candidate, unlike every other local-probe
site. Both retained the multi-second dual-stack IPv6 connect penalty
that _localhost_to_ipv4() exists to skip (measured on macOS: localhost
32.9ms vs 127.0.0.1 0.1ms on a dead port; ~2s on Windows). normalized
stays the cache key so caching behavior is unchanged; only the outbound
request target is rewritten.
Re-derived from PR #61528 onto current main (original no longer applied
cleanly).
- Short-circuit the candidate waterfall on HTTP 401/403: an auth wall
proves the endpoint family exists, so probing the alternate URL just
doubles the wasted wait (the reported endpoint takes ~10s to return
401 without a key).
- Stream the probe so 4xx never downloads a slow error body; responses
are closed on every exit path.
- Regression tests: single-call assertion on 401/403 (fails on main),
negative-cache reuse, 404 waterfall preserved, no .json() on 4xx.
Fixes#69905
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Review pass 2 (reuse reviewer HIGH): the step-3b probe-down fallback for
custom/local endpoints returns the same silent 256K default but only
logged at INFO - invisible by default, and it is the MORE common path
for small local models (the exact users the warning exists for).
Extract _warn_context_length_fallback() (deduped per model+base_url)
and call it from both fallback sites, per the fix-the-whole-bug-class
rule. Regression test drives the custom-endpoint path and fails without
the widening (mutation-checked).
Review follow-up:
- Warn once per (model, base_url) at the step-9 fallback via a module-level
dedup set (established _WARNED_* idiom). The fallback result is
deliberately never cached, so the un-deduped warning fired on every
resolution - e.g. once per gateway message via the session-hygiene path.
- Replace the three inline-mock pool-cleanup tests (which reproduced the
try/except block against a MagicMock and passed even with the production
code reverted) with a parametrized test that drives the real
BatchRunner.run() with a patched Pool; drop the CPython stdlib
signature change-detector test.
- Add a once-per-model warning regression test; clean up dead imports.
All tests verified to fail against pre-PR batch_runner.py/model_metadata.py
and pass with the fix (mutation check).
Salvage of #6629 by aaronlab (kshitijk4poor reworked against current main).
Three concerns from the original PR, reworked to address review feedback:
1. Context-length fallback diagnostic (agent/model_metadata.py):
get_model_context_length() silently returned 256K when all 9 detection
methods failed. Users with small-context models (8K, 32K) would get 256K
silently, causing hard-to-debug API context-length errors. Added a
warning log at the step 9 fallback with model name, base_url, and the
correct config override hint (model.context_length, not context_length).
The token-estimation ceiling-division fix from the original PR already
landed on main (5c2ecdec) with CJK handling — not duplicated here.
2. Fsync for batch trajectory writes (batch_runner.py):
Trajectory entries were written without flush/fsync, but the checkpoint
immediately marked them as completed. A crash between write and disk
sync would leave the checkpoint claiming completion with no trajectory
data on disk. Added flush() + os.fsync() before checkpoint update.
3. Pool cleanup on interruption (batch_runner.py):
Ctrl+C during pool.imap_unordered() relied on context manager cleanup
which can hang. Added explicit pool.terminate() + pool.join() for both
KeyboardInterrupt and Exception paths. The original PR used
pool.join(timeout=10) which is invalid — CPython's Pool.join() takes
no timeout parameter. Fixed to use pool.join() without arguments.
Tests:
- test_warning_emitted_on_fallback: verifies warning fires at step 9
- test_no_warning_when_cached: verifies no false warning when cache hits
- test_trajectory_entry_is_synced_to_disk: verifies os.fsync is called
- test_pool_terminate_called_on_exception: verifies cleanup on RuntimeError
- test_pool_terminate_called_on_keyboard_interrupt: verifies cleanup on Ctrl+C
- test_pool_join_called_without_timeout: verifies no timeout arg to join()
- test_real_pool_join_accepts_no_timeout: integration check on CPython API
Co-authored-by: Aaron Lab <aaronlab@users.noreply.github.com>
The reasoning_details field (OpenRouter/Anthropic thinking blocks +
opaque cryptographic signature blobs) inflates the rough token estimate
by ~4x. Providers do not bill these envelope bytes as prompt tokens.
In a measured Kimi K3 session, reasoning_details held 2,124K chars
vs 281K chars of actual thinking text. The estimator reported ~533K
tokens when real prompt_tokens was ~140K — triggering compression at
~27% of the configured threshold.
Fix: skip reasoning_details in both _estimate_message_chars and
_estimate_message_tokens_without_images, alongside the existing
_anthropic_content_blocks exclusion.
Fixes#73298
Review follow-up on #75102. The shadow substituted the sidecar whenever
the ``api_content`` key was merely PRESENT, but the wire only substitutes
a non-empty string sidecar on a user/assistant row (see
``turn_context.substitute_api_content``). For any other shape the sidecar
is popped and discarded while the clean ``content`` is sent -- so the
shadow dropped real content from the estimate and UNDERcounted, the
dangerous direction: compaction fires too late and the turn dies on a
hard context-length error instead of merely compressing early.
Gate the substitution on the same predicate, and cover the divergent
shapes (None, empty string, int, list, non-user/assistant role) with a
test that fails against the unconditional version.
Also rename the image test: it never carried a sidecar, so it was not
testing what its name claimed. It is a non-regression pin on the flat
per-image accounting that moved into ``_wire_message_shadow()``, and is
now named for that.
`api_content` is a SUBSTITUTE for `content`, not an addition to it.
`turn_context.substitute_api_content()` pops the sidecar and overwrites
`content` at every API-bound message-build site (the `api_messages` build
in `conversation_loop`, the max-iterations summary in
`chat_completion_helpers`, the chat-completions transport), so exactly one
of the two is ever sent to the provider.
The preflight estimator counted both, because both `_estimate_message_chars`
and `_estimate_message_tokens_without_images` walked every key of the
persisted dict with a single-entry denylist (`_anthropic_content_blocks`).
Any message whose sidecar differs from its clean stored content was counted
twice — exactly 2.00x on a 40KB sidecar.
The sidecar exists to keep the provider prompt-cache prefix byte-stable, so
it is written on precisely the long, cache-pinned messages where the
doubling hurts most. Because `estimate_messages_tokens_rough()` also feeds
the compaction threshold via `context_compressor` and `conversation_loop`,
the inflated estimate makes compression fire on phantom bytes.
Fix: substitute rather than sum, mirroring the wire. The two estimator
helpers had drifted into near-identical copies of the same shadow-building
loop, so this factors the shared logic into `_wire_message_shadow()` and
fixes the class once instead of patching one site and leaving the other.
Image accounting is unchanged: base64 payloads are still replaced with a
placeholder and charged at the flat `_count_image_tokens` rate, and the
`_multimodal` text_summary path is preserved.
Tests: three cases in `TestEstimateMessagesTokensRough` — sidecar equal to
content is counted once, a sidecar that DIFFERS is still counted (a lower
bound, so it fails if the field were dropped rather than substituted, which
would undercount the real request), and a sidecar cannot smuggle raw base64
past the flat image rate.
Verified on Linux (Python 3.11): 53 passed in
tests/agent/test_model_metadata.py, 57 passed with
tests/agent/test_context_breakdown.py, 656 passed / 3 skipped across the
compression/context/token/estimate/prune surface of tests/agent.
Mutation-tested: reverting the substitution fails the new equality test.
`scripts/check-windows-footguns.py` is not applicable — no file I/O,
process management, terminal handling, subprocesses, or signals.
Three provably-safe optimizations for O(n)-per-iteration history walks:
1. sanitize_tool_call_arguments: optional identity-keyed cursor (strong
refs to the exact validated message objects) skips re-json.loads-ing
already-validated history each loop iteration. Any list rewrite
(compression, repair, undo, steer) breaks the identity prefix match
and forces re-scan from the divergence point. Wired via a per-agent
cursor dict in conversation_loop.
2. estimate_messages_tokens_rough: per-message memo keyed on a deep
identity fingerprint (strings pinned by strong reference so id()
aliasing is impossible; scalars by value; dicts/lists structurally
with key order). Equal fingerprints imply identical str(shadow)
bytes, hence identical estimates. Unfingerprintable shapes fall
through to direct compute. Bounded FIFO cache (4096 entries).
3. _flush_messages_to_session_db_unlocked: bounded scan that skips the
identity-matched prefix of the previous successful flush's snapshot.
Snapshot only taken on full success; cleared on exception. Compression
rewrites use fresh copies, breaking identity and forcing full re-scan.
Parity proven in tests/agent/test_cursor_optimizations_parity.py:
500-message synthetic histories with tool calls, malformed args, unicode,
element-wise old==new across 3 iterations incl. simulated compression.
Measured (median of 5): sanitize 0.097ms->0.011ms, tokens 1.145ms->0.853ms,
persist-scan 179.5us->10.0us at 500 messages.
Four deferrals following the established truthy-skip / PEP 562
lazy-load patterns (PRs #22681/#22859 lineage). Rebased over #74194,
which independently landed the browser_tool half of this work — that
file is dropped here; the remaining four modules are untouched by it:
- tools/vision_tools.py: defer agent.auxiliary_client
(credential_pool -> hermes_cli.auth -> httpx -> rich, ~50 ms) to
first vision handler call. async_call_llm /
extract_content_or_reasoning stay patchable module attributes;
injected test mocks win over the loader.
- agent/model_metadata.py: defer 'requests' (+urllib3, ~27 ms of the
'import cli' waterfall) to the fetch functions. PEP 562 __getattr__
keeps patch('agent.model_metadata.requests.get') working.
- tools/browser_supervisor.py: websockets (~22 ms) imports on first
CDP connect; ClientConnection type under TYPE_CHECKING.
- cron/jobs.py: croniter (~15 ms) resolves on first cron-expression
use; HAS_CRONITER stays monkeypatchable (None = unprobed sentinel).
A/B vs current main incl. #74194 (median of 7, cold subprocess):
import cli 147 -> 132 ms (-10%)
import model_tools 244 -> 224 ms (-8%)
import run_agent 264 -> 244 ms (-8%)
Lazy-verify: importing the four modules no longer pulls requests /
croniter / websockets into sys.modules. 369 targeted tests green
post-rebase.
Local-model users paid a fresh probe waterfall on EVERY CLI cold start
inside AIAgent.__init__: detect_local_server_type (up to 4 HTTP GETs,
2s timeout each on a hung server) + /api/show (3s timeout). The
existing caches were in-process only, so back-to-back invocations
(chat -q, cron ticks, subagents) re-paid the network every time.
- New 300s-TTL disk L2 at HERMES_HOME/cache/local_endpoint_probes.json
for detect_local_server_type verdicts and query_ollama_num_ctx
results. Only SUCCESSFUL probes persist (a down server never pins a
negative verdict); stale entries pruned on write; corrupted cache
degrades to a miss; atomic writes. 300s is strictly fresher than the
1h in-process TTL that already accepts server-swap staleness.
- models.dev fetch timeout 15 -> (5, 10) connect/read tuple: a
blackholed connect stalled the first-turn critical path 15s; now
fails in 5s (matches the OpenRouter fetch convention, #46620).
- _auto_detect_local_model timeout 5 -> (2, 3): runs inside
_get_model_config() at startup against a LOCAL endpoint; a hung local
server cost 5s before the banner.
E2E (real HTTP server, two fresh subprocesses, isolated HERMES_HOME):
proc1 = 2 HTTP hits, proc2 = 0 HTTP hits, identical results
(ollama/131072), probe wall 74.5 -> 35.5 ms. 222 targeted tests green
incl. 9 new disk-L2 contract tests.
Anthropic released Claude Opus 5 (+ -fast variant) — both are live on
OpenRouter and the Nous Portal /models endpoint (verified against both
live APIs). Opus 4.8 entries are kept.
- hermes_cli/models.py: opus-5 + opus-5-fast in OPENROUTER_MODELS;
opus-5 in _PROVIDER_MODELS[nous] (Portal serves both, curated list
carries the base model like the rest of the Nous Anthropic block).
Ordering: below fable-5 flagship, above opus-4.8.
- agent/model_metadata.py: claude-opus-5 -> 1M context (matches live
OpenRouter metadata).
- agent/reasoning_timeouts.py: claude-opus-5 -> 240s stale-timeout
floor (same as the opus-4.x thinking family).
- website/static/api/model-catalog.json: regenerated via
scripts/build_model_catalog.py.
Both providers bill via official_models_api (live pricing), so no
_OFFICIAL_DOCS_PRICING snapshot entry is needed for these routes.
The salvaged estimator ran a per-character Python loop on every
estimate_tokens_rough() call — a ~28,000,000x slowdown vs (len+3)//4 on a
1MB ASCII tool output (measured ~3.0s per call). Gate it:
- str.isascii() O(1) fast path keeps pure-ASCII text bit-identical to the
classic (len+3)//4 rule at ~1.3x baseline cost (0.23us vs 0.17us per
1MB call).
- Non-ASCII text counts dense CJK chars via a compiled character-class
regex in C (len(text) - len(re.sub(''))): ~352ms/1MB hangul vs ~2.1s
for the per-char loop.
- Non-ASCII-but-non-CJK text (accents, Cyrillic, emoji) keeps the classic
rule.
Also: parity tests against the per-char reference implementation, and
updated two stale expectations that encoded the old behavior (CJK now
counted ~1 token/char; short string content now ceil-divided instead of
floored to 0). The continuity test now detects merged-into-tail summaries
via _is_context_summary_content.
The Codex backend returns the per-account model catalog only when the
ChatGPT-Account-Id header is present. Without it, GET /backend-api/codex/models
responds 200 OK with {"models":[]} and the picker silently degrades to the
hardcoded fallback list — which is stale or wrong for the active plan
(no GPT-5.6 family, wrong context windows).
This was the upstream bug behind slow first responses and HTTP 520/120s SSE
hangs: Hermes was sending invalid slugs because the probe never saw them in
the catalog, and Codex's request builder also depends on the same JWT claim
that's now being threaded through both probe paths.
Fixes the probe-side paths in hermes_cli/codex_models.py and
agent/model_metadata.py by extracting chatgpt_account_id from the OAuth JWT
(mirroring the request-side logic already in auxiliary_client.py) and sending
it as a header.
Verified live:
- _fetch_models_from_api now returns the 10-model catalog (gpt-5.6-sol,
gpt-5.6-terra, gpt-5.6-luna, gpt-5.5, gpt-5.4, gpt-5.4-mini,
gpt-5.3-codex-spark, 3x -pro variants) instead of [].
- _fetch_codex_oauth_context_lengths resolves all 8 account models to 272K
context (matches direct API probes of the same account).
- end-to-end: hermes chat -m gpt-5.6-sol -q 'Reply with one word: pong'
returns 'pong' cleanly via the openai-codex route.
Same class of bug as PR #64760.
Follow-up widening for salvaged PRs #67115, #67685, #67620:
- _PROVIDER_MODELS: add kimi-k3 atop kimi-coding / moonshot / opencode-go
curated lists (kimi-coding-cn covered by cherry-picked #67620)
- setup.py _DEFAULT_PROVIDER_MODELS: kimi-k3 for kimi-coding(-cn) + opencode-go
- model_metadata: align DEFAULT_CONTEXT_LENGTHS kimi-k3 entry to 1,048,576
(matches endpoint-scoped override, models.dev, and OpenRouter live metadata)
- anthropic_adapter: classify the bare Coding Plan slug 'k3' (and k3.x/k3-*)
as Kimi family so adaptive thinking applies on proxied endpoints
- moonshot_schema: is_moonshot_model matches bare 'k3' so tool-schema
sanitization runs on the chat-completions path
- contributor mappings for githubespresso407, datachainsystems, Punyko8
Tests: 582 passed across 11 targeted files; hermetic E2E verifies picker
order (kimi-k3 first), no dupes, and 1M context resolution.
Kimi K3 ships with a 1M-token context window (verified against
platform.kimi.ai/docs/overview) but was falling through to the generic
'kimi': 262144 catch-all. Added 'kimi-k3': 1_000_000 before the catch-all
so longest-key-first substring matching resolves K3 to 1M while older
Kimi models still hit the 256K default.
Added matching test_kimi_k3_context_1m test covering native,
vendor-prefixed (kimi/, moonshotai/), and older model fallback.
Kimi Coding serves K3 under the bare slug 'k3', but users can also
configure or select the public-facing aliases 'kimi-k3' and
'kimi-k3-cot'. The endpoint-scoped 1M context window was only keyed
on the bare 'k3' slug, so selecting 'kimi-k3' fell through to the
generic 'kimi' catch-all (262k).
Extend the guard in _endpoint_scoped_context_length to also recognize
'kimi-k3' and 'kimi-k3-cot', while keeping the endpoint check that
limits the 1M value to https://api.kimi.com/coding (legacy Moonshot
endpoints still fall back to 262k). Update the existing test to cover
all three aliases.
Fixes: context window limited to 262k when using kimi-k3 via kimi-coding.
- The #44861 stale-cache guard invalidated any cached value that differed
from the static table, which would have discarded legitimate
probe-derived windows larger than the table. Treat the table as a
FLOOR: only drop under-reporting cache entries.
- Update probe test fixtures that predated the 4.6+ 1M table flip
(opus-4-6 fallback expectations 200K -> 1M).
Bedrock models resolved their context window from a hardcoded table
(BEDROCK_CONTEXT_LENGTHS) keyed by longest-substring match. AWS ships
new model versions faster than the table tracks, so a new model like
claude-opus-4-8 (1M-token window) silently matched the older
"anthropic.claude-opus-4" entry and got capped at 200K — wasting 80%
of the available context.
Bedrock exposes the real window nowhere in metadata: get-foundation-model
omits it, Converse usage metrics omit it, CountTokens is unsupported on
several models. The only authoritative source is the ValidationException
raised when a prompt exceeds the window:
"prompt is too long: 1300032 tokens > 1000000 maximum"
Length validation runs before inference, so an oversized request is
rejected immediately and cheaply (no tokens generated, no input
processed). This adds probe_bedrock_context_length(): pad a request just
past a tier, parse the reported maximum, return it. get_bedrock_context_length()
now probes first and falls back to the static table only when the probe
can't run (missing creds, network error, unparseable error). The static
table stays as a safety net.
get_model_context_length() caches the probe result per model+region, so
the network cost is paid once, not every turn. probe=False / empty region
disables probing for offline/display paths — backward compatible with the
single-arg callers.
Verified E2E against live Bedrock (eu-central-1): claude-opus-4-8 resolves
to 1000000. Unit tests cover error parsing, unparseable errors, missing
client, probe-beats-table, and table fallback.
BEDROCK_CONTEXT_LENGTHS was missing entries for current 1M-context Claude
models, and the resolution path in get_model_context_length() short-circuits
to that table (step 1b) before DEFAULT_CONTEXT_LENGTHS is ever consulted, so
the catalog's correct values could never apply on Bedrock:
- claude-fable-5 (no entry at all) fell through to
BEDROCK_DEFAULT_CONTEXT_LENGTH and reported 128K for a 1M model.
- opus-4-7 / opus-4-8 substring-matched the generic 'anthropic.claude-opus-4'
key and reported 200K.
- opus-4-6 / sonnet-4-6 had explicit 200K entries predating their 1M windows.
The practical symptom: the agent compresses context prematurely (at ~128K or
~200K of a 1M window) on every Bedrock-hosted current Claude model.
Fixing the table alone is not enough for existing installs: a previously
persisted 128K/200K value in the context-length cache wins at step 1 and
masks the corrected table forever. Step 1 now reconciles Bedrock-context
cache hits against the static table (the table is authoritative for Bedrock
— there is no live probe to reconcile against), invalidating stale entries
so existing users converge to the right window without manual cache surgery.
Tests cover the new table entries (incl. inference-profile and versioned ID
forms), the 128K-default regression for Fable, the stale-cache invalidation
path, and that pre-4.6 models keep their 200K entries.
Follow-up to the salvaged #66083/#42792 commits:
- alibaba (Qwen Cloud coding-intl) gets qwen3.7-plus too — same platform
allowlist as alibaba-coding-plan (issue #44662 comment by @coder-movers)
- qwen3-max substring context entry (262144) so the newly-listed
qwen3-max-2026-01-23 snapshot doesn't fall to the generic 131072 qwen
fallback
Add qwen3.7-plus to DEFAULT_CONTEXT_LENGTHS with 1M context window.
Without this entry, the model falls back to the generic 'qwen' entry
(128K), causing premature context compression at 50% (64K tokens)
instead of the correct 500K threshold.
Official docs: https://help.aliyun.com/zh/model-studio/developer-reference/
Pin the Upstage default to the concrete solar-pro3 instead of the
solar-pro rolling alias:
- plugin fallback_models is now ("solar-pro3",); entry [0] is the setup default
- drop the "solar-pro" context-window fallback entry (solar-pro3 covers it)
- update the reasoning default-on docstring and profile tests accordingly
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Remove the `solar-open2-preview` context-window entry; `solar-open2`
covers the Open 2 family at the same 256K window.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Adds Upstage Solar as a bundled model-provider plugin. Solar exposes an
OpenAI-compatible chat-completions endpoint at https://api.upstage.ai/v1, so
the generic chat_completions transport handles request/response/streaming/tool
calls — the profile is the core integration.
Provider registration (Upstage isn't in models.dev, so each registry that does
not auto-wire from the plugin layer needs an explicit entry — same pattern as
nvidia/gmi):
- plugins/model-providers/upstage/: UpstageProfile + plugin.yaml. Picker default
and offline catalog list only the agentic Solar Pro models, led by `solar-pro`
(rolling alias for the latest Pro). default_aux_model empty so aux tasks use
the main model. `solar` alias. UPSTAGE_BASE_URL overrides the host.
- hermes_cli/providers.py: HERMES_OVERLAYS + label + `solar` alias, so
resolve_provider_full('upstage') resolves (without this, an explicit
`provider: upstage` in config was dropped and fell through to auto-detect).
- hermes_cli/auth.py: PROVIDER_REGISTRY entry + `solar` alias, so `hermes
doctor` / resolve_provider recognise upstage (the static-registry path the
lazy profile-extension doesn't reliably cover at validation time).
- hermes_cli/models.py: CANONICAL_PROVIDERS entry places Upstage Solar in the
curated picker order (above the auto-appended `custom`).
- agent/model_metadata.py: context-window fallbacks (/v1/models omits
context_length); `solar-pro` carries the 128K Pro context as the catch-all.
Reasoning: UpstageProfile.build_api_kwargs_extras wires Solar's top-level
`reasoning_effort` (low|medium|high; xhigh/max→high). Reasoning-capable families
are solar-pro* and solar-open*; solar-mini/syn-pro never receive it. Defaults ON
at medium when unset (matches the /reasoning "medium (default)" label);
`/reasoning none` disables; explicit/saved settings are honored. No
reasoning_content echo handling needed (unlike DeepSeek/Kimi).
Web dashboard:
- web/src/pages/EnvPage.tsx: add an "Upstage Solar" provider group so
UPSTAGE_API_KEY / UPSTAGE_BASE_URL appear under LLM Providers (not "Other").
Docs/tests:
- .env.example: documents UPSTAGE_API_KEY / UPSTAGE_BASE_URL.
- tests: profile wiring, reasoning_effort mapping (pro/open/mini, efforts,
disabled, default-on), provider-resolver regression (resolve_provider_full /
get_provider / solar alias / overlay), `solar-pro` default.
Testing: pytest tests/providers tests/plugins/model_providers
tests/hermes_cli/test_upstage_provider.py tests/run_agent/test_provider_parity.py
tests/hermes_cli/test_api_key_providers.py; ruff clean. Verified end-to-end:
`hermes doctor` shows "Upstage Solar", and live chat works via both
`--provider upstage` and `--provider solar`. Reasoning wire format per
https://console.upstage.ai/api/docs/for-agents/raw. Platforms tested: macOS.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The _PROVIDER_PREFIXES frozenset in agent/model_metadata.py is static
and does not auto-extend from ProviderProfile. Removing deepinfra and
deep-infra from it broke provider:model prefix stripping for DeepInfra.
_load_context_cache() returned None when context_length_cache.yaml
contained 'context_lengths:' (no value) — YAML parses this as
{'context_lengths': None} and dict.get(key, default) only returns
the default when the key is absent, not when the value is None.
This caused AttributeError in every downstream caller (issue #47135).
Fix: use 'or {}' instead of default= so both absent key and
None value return an empty dict.
Fixes#47135
Phase-2 review findings addressed:
- resolve_billing_route: normalize the "openai-api" picker slug to the
"openai" billing provider — without this the ("openai", <model>)
_OFFICIAL_DOCS_PRICING keys (incl. every pre-existing gpt-4o/gpt-4.1
entry, not just 5.6) were unreachable when the provider is openai-api.
- pricing_version: drop the "preview" tag (GA 2026-07-09 at same rates).
- model_metadata comment: dict order is cosmetic — lookups length-sort
keys at match time; the old comment implied a positional invariant.
- model_switch comment: note "sol" is a series codename, not a generic
quality word.
- tests/hermes_cli/test_gpt56_registration.py: behavior contracts (no
list snapshots) — sol > terra/luna > 5.5 sort invariant, pricing
reachability from both openai and openai-api routes, cache-write
1.25x / cache-read 0.10x input relation.
PR #61578 added the GPT-5.6 series (sol/terra/luna) to the two aggregator
surfaces (OPENROUTER_MODELS, _PROVIDER_MODELS[nous]). This completes the
registration on the remaining surfaces per the standard add-model checklist:
- agent/model_metadata.py: DEFAULT_CONTEXT_LENGTHS 1.05M (direct API, same
as gpt-5.5; more-specific keys precede gpt-5.5 for longest-substring
matching) + _CODEX_OAUTH_CONTEXT_FALLBACK 272K for all three slugs.
Without these the direct-API fallback matched generic "gpt-5" = 400K.
- hermes_cli/codex_models.py: DEFAULT_CODEX_MODELS + forward-compat
templates so ChatGPT-OAuth (openai-codex) pickers surface the series.
- hermes_cli/models.py: _PROVIDER_MODELS[openai-api] (native API picker).
- agent/usage_pricing.py: _OFFICIAL_DOCS_PRICING snapshot — sol 5/30,
terra 2.50/15, luna 1/6 per 1M in/out; cache read 0.10x input, cache
write 1.25x input (OpenAI billing change starting with the 5.6 series).
GA 2026-07-09 at preview rates. Sol Fast mode (Cerebras tier) excluded.
- hermes_cli/model_switch.py: rank "sol" as a flagship suffix so
/model gpt resolves to gpt-5.6-sol, not alphabetical-first luna.
Verified: registry E2E via real imports (both context tables, codex
forward-compat from a gpt-5.5 template, billing-route lookup for
openai/gpt-5.6-sol -> 5.00/M), alias resolution on openai-codex and
openai-api resolves to gpt-5.6-sol; 183 targeted tests pass
(model_metadata, usage_pricing, codex_models, model_catalog).
Structured review (2a/2b/2c) findings, all fixed:
- MAJOR: detect_local_server_type memo was process-lifetime with no
invalidation, permanently pinning a URL's server type. Now a bounded
1h TTL ((type, monotonic) tuples) so a backend swap on the same port
is re-detected. Test covers ollama->lm-studio swap after expiry.
- MAJOR: legacy disk-row compat was one-way. get_cached_context_length
and _invalidate_cached_context_length now consult the same key-shape
set {canonical, literal, canonical+slash} in both directions, so an
old slashed row is found (and cleared) when the runtime passes the
normalized URL. Tests pin both migration directions.
- MINOR: _localhost_to_ipv4 did whole-string replacement, which could
corrupt a proxy URL embedding http://localhost in its query. Now a
scheme-anchored host-only regex; localhost.example.com and embedded
substrings pass through. Tests added.
- MINOR: _invalidate_cached_context_length now also drops the
in-memory TTL probe rows for the pair, so a resolution inside the
TTL window can't re-persist the value just declared stale.
- Test gaps closed: detect-type cache hit + TTL-expiry re-detection,
ollama-show TTL expiry re-probe, reverse legacy-row lookups.
- Attribution gate: added zhchl@hermes-agent.local -> 8294 (PR #50572
author) to AUTHOR_MAP; the strict CI grep needs bare non-plus emails
literal in release.py.
Gates: ruff clean; targeted suites 202 passed / 0 failed; full
tests/agent 5426 passed with 17 failures identical on clean
upstream/main (pre-existing env-dependent anthropic/bedrock/credpool
tests); mypy delta vs base: 0 new errors; live smoke 6/6 PASS.
#37595 fixed the Windows dual-stack IPv6 timeout only inside
detect_local_server_type. The same 2s-per-probe penalty existed at every
other helper that builds a probe URL from base_url. Extract the rewrite
into _localhost_to_ipv4() and apply it at:
- query_ollama_num_ctx
- query_ollama_supports_vision
- _query_ollama_api_show (server_url derivation)
- _query_local_context_length (server root + LM Studio native URL)
Tests cover the helper's URL forms, non-localhost passthrough, and that
the ollama probes actually POST to 127.0.0.1.
Follow-up hunks completing the probe-cache cluster:
1. _query_ollama_api_show now goes through the existing
_LOCAL_CTX_PROBE_CACHE (30s TTL, positive-only, namespaced key) —
it was the one remaining per-resolution POST not covered by the
#56431-era wrapper. Failures are never memoized so a server that
comes up mid-startup is re-probed. Idea credit: #42081 (@Morad37),
reworked to comply with the positive-only rule.
2. Persistent context-cache keys are normalized through
_context_cache_key (trailing-slash strip) so http://host/v1 and
http://host/v1/ share one entry; reads and invalidation honor
legacy un-normalized rows. Idea credit: #37905 (@stevenau21).
Tests: TTL hit collapses to one POST, failure-not-memoized
(mutation-verified: unconditional caching makes it fail), namespace
no-collision vs the sibling probe, slash-variant dedup, legacy-row
read, dual-shape invalidation.
_cli's show_banner() calls _resolve_active_context_length() at every
startup. For non-OpenRouter providers (e.g. minimax-cn, kimi-coding,
custom endpoints) the resolver falls through to step 6 (OpenRouter
live /models fetch), which blocks ~2-3s per CLI launch and adds up
to 7+ minutes when openrouter.ai is unreachable through a proxy that
403s CONNECT (#46620).
Two complementary changes:
1. model_tools.py: read model.context_length from config.yaml and pass
it as config_context_length to get_model_context_length. The
step-0 config override short-circuits the entire resolution chain
including the OpenRouter fetch. No network call is made when the
user has set the value explicitly.
2. agent/model_metadata.py: replace flat timeout=10 with (5, 10)
tuple at all five sites (fetch_model_metadata + four endpoint
probes). urllib3 can otherwise block for 10s per retry stage
through proxies that 403 CONNECT. The tuple bounds connect at 5s
while still allowing slow reads.
Complements the in-flight PR #46685 (which adds HERMES_DISABLE_MODEL_METADATA
env var + same timeout tuple change for fetch_model_metadata). This PR
extends the timeout fix to the other four endpoint probes and adds the
config-override path that addresses the slow-but-reachable scenario
where env-var disable is too heavy-handed.
Refs #46620, PR #46685.
(cherry picked from commit e7faa34199)
On Windows, `localhost` resolves to both ::1 (IPv6) and 127.0.0.1 (IPv4).
httpx tries IPv6 first, hanging 2 sec per probe when the server binds IPv4
only. detect_local_server_type() is called 3+ times during init, each with
a new httpx.Client, compounding to ~14s of dead time.
Replace localhost with 127.0.0.1 inside the function before connecting.
The function is only called for local endpoints (callers guard with
is_local_endpoint()), so IPv6 loopback adds no diagnostic value.
Measured: 19.9s → 4.0s on Windows with a local proxy on 127.0.0.1:8317.
(cherry picked from commit a075d3194b)
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