Flips the default fan-out cadence from per_iteration (advisors re-run on
every tool iteration, multiplying advisor spend by tool-loop depth) to
user_turn (advisors run once on the first message of each user turn; the
acting aggregator works the rest of the tool loop with that turn's
advice). Until per-mode benchmarks justify a costlier default, MoA
defaults to the cheapest, lowest-impact cadence (#67199).
One default for everyone — no split legacy/new-preset semantics; presets
that want per-step advising set fanout: per_iteration explicitly. All
three modes (user_turn / per_iteration / every_n:N) remain selectable;
every_n:1 still collapses to per_iteration (semantic identity), while
unparseable values now fall to user_turn (the default).
Docs updated with a default-change note; the per-iteration rerun test
pins its mode explicitly.
Co-authored-by: skyer-flyyy <188930297+skyer-flyyy@users.noreply.github.com>
_render_tool_calls only handled dict-shaped entries; a SimpleNamespace-
shaped tool_call (SDK-style stream-stitched responses) rendered as
'[called tool: tool]', silently losing the function name and arguments
from the advisory view. Handle both shapes (including a namespace-shaped
nested function inside a dict entry).
One-hunk hardening salvaged from closed#59712.
Co-authored-by: SquabbyZ <601709253@qq.com>
Reference models may have a smaller context window than the aggregator
(e.g. kimi-k2.7-code @ 262K advising a glm-5.2 @ 1M conversation).
Without context-length protection, a reference whose window is exceeded
gets a hard HTTP 400 from the provider, which _run_reference's
try/except silently converts to a [failed: …] note — the MoA turn
silently degrades to fewer references (#60345).
Redesigned implementation of #60387:
- Estimate AFTER the advisory system prompt is prepended, so the
request that is actually sent is what gets budgeted.
- Reserve output headroom: the preset's reference_max_tokens when set,
else an 8192-token constant, plus a 10% estimator-error fraction.
- Trim on advisory-view boundaries (text-only user/assistant turns; no
tool-result frames to orphan), preserving the system prompt, the
user-first invariant after every pop (never assistant-first), and the
trailing synthetic user turn.
- Cache get_model_context_length per (provider, model) in a per-fan-out
dict shared across the worker threads, so a turn resolves each
window once instead of probing metadata sources
per-reference-per-iteration (failures are cached too).
Co-authored-by: webtecnica <75556242+webtecnica@users.noreply.github.com>
Follow-ups for salvaged #56344:
- A reference that completes between the interrupt check and the reap
keeps its REAL output and accounting (the provider call billed) instead
of being zeroed with a placeholder.
- A reference still in flight at interrupt time gets a placeholder in the
results, but its future now carries a done-callback that folds the
eventual real usage/cost into the facade's pending accounting
(late_accounting_sink -> _record_late_reference_accounting), so billed
spend is never silently dropped. Pending totals are folded (not
overwritten) and guarded by a lock since done-callbacks fire on
executor worker threads.
- Interrupted placeholder results are no longer written into the facade's
turn-scoped reference cache: a cache HIT never re-runs references, so
caching a partial snapshot would replay '[skipped: interrupted by
user]' notes for the rest of the turn. The cache is left empty and the
next create() re-runs the fan-out.
agent/tool_executor.py's concurrent tool batch checks agent._interrupt_requested
and aborts the wait early; agent/moa_loop.py's _run_references_parallel had
no equivalent, so a MoA-enabled turn blocked on ThreadPoolExecutor.result()
until every reference model finished or hit its own individual
auxiliary.moa_reference timeout -- there was no way for the user to abort a
live turn mid-fanout.
Thread an optional `agent` parameter through aggregate_moa_context ->
_run_references_parallel (used when MoA references run alongside the main
model) and MoAClient/MoAChatCompletions (used when the MoA preset itself is
the acting model), then poll concurrent.futures.wait() in
_REFERENCE_POLL_INTERVAL_S slices instead of blocking on future.result() per
reference, checking agent._interrupt_requested each cycle.
Deliberately scoped to interrupt/cancel only -- no new or changed timeout
value, so this doesn't overlap open PRs #53784/#53875 (which lower the
per-reference timeout default but don't add interrupt support). `agent` is
optional and defaults to None, so any caller that doesn't pass it keeps
today's uninterruptible blocking behavior unchanged.
Extends the all-references-failed short-circuit (#56975) to the
persistent `provider: moa` facade path: MoAChatCompletions.create()
previously attached 'use the reference responses below' guidance built
entirely from failure sentinels and called the aggregator with it. Now
an all-failed turn attaches either the sanitized unavailability notice
(loud policy) or nothing (silent policy), and the aggregator — which IS
the acting model — simply acts alone. Advisor accounting for the failed
fan-out is still recorded.
Co-authored-by: liuhao1024 <sunsky.lau@gmail.com>
When every MoA reference model returns a failure (HTTP error, timeout,
etc.) or is skipped by the recursion guard, the one-shot aggregator
synthesis call is now skipped entirely. Previously it would try to
synthesise a wall of failure sentinels, which could block for the full
provider timeout (observed ~6 min on SenseNova) before returning a
non-retryable error that left the session hanging.
The early return carries the sanitized unavailability notice (never raw
provider error text, per the failed-reference containment) so the main
agent loop can still act in single-model mode.
Salvaged from #56975, reworked atop the _is_failed_reference helpers.
Follow-ups for salvaged #53784:
- reference_timeout now defaults to None = no per-preset override, so the
reference fan-out inherits auxiliary.moa_reference.timeout (900s default)
via call_llm's own per-task timeout resolution. The PR's 30.0s default
would have cut off long-thinking advisors mid-response, and its 300s max
cap capped legitimate explicit values — both removed. Explicit per-preset
values are still honored as-is.
- _is_failed_reference also treats '[skipped: …]' recursion-guard notes as
internal sentinels, keeping them out of both aggregator prompts.
- Dashboard/desktop TS types updated to number | null; web_server validator
accepts null/empty as 'inherit'.
Adds test_moa_gemini_aggregator_sanitize_uses_real_model: drives a full MoA
tool-call turn (virtual-provider mode) with a Gemini aggregator and asserts
the strict-API sanitize pass is invoked with the resolved aggregator model
(gemini-3-pro-preview), never the virtual preset name once a slot is
resolved — the exact path that stripped extra_content/thought_signature and
made Gemini aggregators 400 (#65092).
Writing the test surfaced a gap in the salvaged #66212 fix: in virtual-
provider MoA mode (provider=moa, no moa_config threaded through
run_conversation) the conversation-loop branch never fired because it only
consulted moa_config. Extend it to fall back to the facade's
last_aggregator_slot — the same source the handle_max_iterations fix uses —
so both MoA entry modes resolve the real aggregator model.
Also adds the contributors/emails mapping for the #15676 credit base.
Follow-ups to the salvaged core of #60293:
- Gate the x-initiator header on _normalize_aux_provider() instead of a
literal 'copilot' string compare, so slot configs spelled github /
github-copilot / github-models / copilot-acp / mixed case all get the
user-turn attribution.
- Thread extra_headers through _retry_same_provider_sync/_async so the
credential-refresh and pool-rotation retry rebuilds don't silently drop
the header (the rebuilt kwargs previously started from scratch).
- Add a transport-boundary test asserting the header reaches the SDK
client's create() kwargs (no call_llm mocking), an alias-spelling
matrix test, and a retry-rebuild preservation test.
Follow-up to the salvaged core of #53802: a naive MoAClient(preset) rebuild
restores a working facade but silently drops the reference_callback relay
wired in agent_init, so moa.reference / moa.aggregating display events stop
reaching every frontend for the rest of the session.
Introduce agent.moa_loop.build_moa_facade(agent, preset) as the single
construction point for the MoA facade and use it at:
- initial client construction (agent_init.py)
- turn-start fallback restore (restore_primary_runtime)
- transient transport recovery (try_recover_primary_transport — previously
fell through to _create_openai_client with MoA's empty client_kwargs and
died with 'api_key client option must be set')
- mid-session model switches (switch_model)
The relay reads agent.tool_progress_callback at emit time, so callbacks
attached after construction are picked up automatically.
Adds test_moa_restored_facade_still_emits_reference_events covering event
delivery through a restored facade.
Follow-up to the cherry-picked empty-user-turn drop: the placeholder
introduced in 8582f35d9 fired for whitespace-only STRING turns too
(content=' ' flattens to non-stripping text but isn't in the
(None, '', []) exclusion set), fabricating an attachment note for a turn
that carried nothing. Gate the placeholder on isinstance(content, list)
so only genuinely structured (e.g. image-only) turns get it; empty and
whitespace-only string turns now fall through to the drop path.
Edge cases verified: trailing empty user turn still ends the view on the
synthetic advisory marker; an all-empty transcript degenerates to [].
MoA's _reference_messages() unconditionally appended every user-role
message to the advisory view sent to reference models, even when the
message content was an empty string or a non-string/multimodal payload
that the text-extraction step flattens to "".
Strict providers (Kimi/Moonshot, and others that enforce non-empty user
content) reject such a message with:
400 Invalid request: the message at position N with role 'user'
must not be empty
Lenient providers (DeepSeek) accept it, so an identical rendered view
passes on one reference and 400s on another within the same fan-out —
the user sees "kimi doesn't support MoA" when the real cause is an empty
user turn leaking into the advisory transcript.
Skip empty user turns, mirroring the existing behavior for empty
assistant turns (which are already dropped when they carry no parts).
The end-on-user invariant is preserved: the synthetic advisory-request
user turn is still appended when the view would otherwise end on an
assistant turn.
Adds a regression test asserting the advisory view contains no empty
user turn and still ends on a user turn.
Cache-decorated turns (apply_anthropic_cache_control converts string
content to [{type: text, ..., cache_control}] lists — applied BEFORE the
MoA facade since the #57675 cache-cold fix) and multimodal turns
(text + image_url parts) flattened to empty strings in
_reference_messages, which only read str content. On turn 1 of a
provider:moa session with a Claude aggregator the references received a
single EMPTY user message: Anthropic-side providers 400'd ('messages: at
least one message is required') while tolerant models answered 'no user
request is present' (live incident Jul 14 2026, preset 'closed').
Fixes, in totality:
- _reference_messages: extract visible text via
agent/message_content.flatten_message_text for user/assistant/tool
turns (skips image parts, so no base64 leaks into the advisory view);
decorated and undecorated transcripts now produce a byte-identical
advisory view (advisor cache prefix stays stable).
- image-only user turns get a placeholder instead of an empty message
(Anthropic rejects empty text blocks) or a silently dropped turn
(would break user/assistant alternation).
- degenerate-case fallback flattens structured content too.
- _attach_reference_guidance: a decorated/multimodal trailing user turn
now receives the guidance as a NEW text part appended AFTER the
cache_control-marked part (cached prefix byte-stable) instead of
falling through to a second consecutive user message (strict providers
reject user/user).
- conversation_loop MoA injection: multimodal user turns get the MoA
context appended as a trailing text part instead of being dropped;
user_prompt for the one-shot path flattens content lists instead of
str()-ing them (which leaked base64 payloads into the prompt).
Live-verified on the 'closed' preset (real OpenRouter wire, 2 user
turns, tool loop): all 4 reference calls carry the full document +
rendered tool state, end on user, zero tool-role/tool_calls; advisor
cache_write 7968 then cache_read 5909+; aggregator cache_read
14880-15237 on iterations 2+.
Co-authored-by: bo.fu <bo.fu@meituan.com>
test_references_run_in_parallel asserted elapsed < 0.9 for two 0.5s
sleeps that run concurrently. On a loaded CI runner, thread-pool
startup pushed the wall time to 0.9001s — a 0.14ms miss — flaking the
shard. Loosen to < 0.95, which still sits well below the 1.0s serial
floor, so a genuine serialization regression (>=1.0s) still fails hard.
The MoA aggregator received the per-turn reference block merged into the most
recent `user` message. In an agentic tool loop that message is the original
task near the top of the context (everything after it is assistant/tool turns),
so injecting text that changes every iteration diverges the prompt prefix early.
The server's KV cache then cannot be reused and the entire conversation
re-prefills on every tool-loop step — full prefill each step, which dominates
latency on long contexts.
Append the reference block at the end of the prompt instead (merging into the
last message only when it is already a trailing user turn, i.e. plain chat).
This keeps the [system][task][tool-history] prefix stable and cache-reusable so
only the new block re-prefills, and gives the aggregator the references with
recency. Extracted as `_attach_reference_guidance` with unit tests.
Measured on a local llama.cpp aggregator over a long agentic task: KV-cache
reuse on follow-up steps went from ~0.3% to ~93-95% and per-step prefill on an
~80k-token context dropped from ~44s to <1s, with no change to output.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Adds moa.save_traces (default off). When on, every MoA turn that runs the
reference fan-out appends one JSON line to
<hermes_home>/moa-traces/<session_id>.jsonl capturing the TRUE FULL turn:
each reference model's exact input messages (system advisory prompt + full
advisory view, not the truncated display preview) + full output + usage +
per-advisor cost, and the aggregator's exact input (including the injected
reference-context guidance block) + output. Lets MoA runs be audited and
improved offline — what every model saw, said, and cost.
- agent/moa_trace.py: config-gated JSONL writer, profile-aware path via
get_hermes_home(), best-effort (never breaks a turn), moa.trace_dir override.
- agent/moa_loop.py: _RefAccounting now carries full input/output/model/
provider/temperature; create() stashes the full turn on a cache MISS
(once per turn, never on the cache-HIT repeat iterations); non-streaming
aggregator output captured inline, streaming marked + pointed at the
session assistant message. consume_and_save_trace(session_id) flushes it.
- agent/conversation_loop.py: flushes the trace with the live session_id
right after MoA usage consumption. No-op for non-MoA clients.
- hermes_cli/config.py: moa.save_traces + moa.trace_dir defaults.
Traces are a side channel — NOT the messages table, never in replay, safe
to delete. Off by default; only overhead when off is one config read on a
MoA cache-MISS turn.
Tests: full-trace-when-enabled (per-ref input+output+cost, aggregator
input-with-guidance + output), nothing-when-disabled. Live E2E through
run_conversation confirmed the loop wiring writes the file.
MoA ran the reference models before the aggregator but returned only the
aggregator's usage to the loop — _run_reference discarded each advisor
response's .usage entirely. Session accounting (state.db, /insights, cost)
therefore undercounted every MoA turn by the whole reference fan-out, which
is usually the bulk of the spend and scales with advisor count.
- _run_reference normalizes each advisor's usage with ITS OWN resolved
provider/api_mode and prices it at ITS OWN model rate (correct cache-read/
cache-write split), returning a _RefAccounting(usage, cost).
- create() sums advisor usage + cost once per turn (cache MISS only, so a
repeat tool-iteration reusing cached advice does not double-charge) and
exposes it via MoAClient.consume_reference_usage().
- conversation_loop folds advisor tokens into the reported/persisted token
counts and adds advisor cost (priced per-advisor) on top of the
aggregator cost, in both the in-memory session totals and the state.db
per-call delta. Aggregator cost is still priced on aggregator-only usage
so advisor tokens are never repriced at the aggregator rate.
- CanonicalUsage gains __add__ for per-bucket summing.
Tests: advisor usage/cost capture, per-turn sum + consume-clears +
cache-hit no-double-charge, CanonicalUsage.__add__.
_slot_runtime maintained a hand-listed name-preservation set
({nous, anthropic, openai-codex, xai-oauth, bedrock}) that returned bare
provider+model to avoid call_llm collapsing an explicit base_url to the generic
'custom' route. That duplicated _resolve_task_provider_model's
_preserve_provider_with_base_url guard (a provider-catalog capability check)
and had to be extended by hand for every provider with custom auth/signing —
the exact drift that produced the anthropic (#54609) and bedrock (#54912) 429/
empty-response bugs.
Removes the whitelist: _slot_runtime now forwards the resolved base_url/api_key/
api_mode for every slot, and the single chokepoint
(_resolve_task_provider_model -> _preserve_provider_with_base_url) decides
identity preservation. Behavior is unchanged for the five providers — their
provider branches (codex Responses+Cloudflare, xai-oauth, bedrock SigV4,
anthropic OAuth Bearer+anthropic-beta, nous Portal tags) re-resolve their own
credentials by name and ignore a forwarded base_url/api_key, so forwarding is
safe even for bedrock's placeholder 'aws-sdk' key.
Verified via real-import E2E: _slot_runtime -> _resolve_task_provider_model
preserves openai-codex/xai-oauth/bedrock/anthropic/nous (+openrouter control) —
none collapse to custom. Tests updated to assert the pipeline invariant against
the real resolver instead of the removed whitelist's bare-return shape.
#54609 moves anthropic into the _slot_runtime name-preservation set (it must
NOT forward base_url/api_key — OAuth sk-ant-oat* needs the provider branch's
Bearer + anthropic-beta header). The pre-existing parametrized
test_moa_provider_backed_slot_survives_aux_resolution still listed anthropic
asserting the forward path, contradicting the new behavior. anthropic is now
covered by test_slot_runtime_anthropic_oauth_routes_through_provider_branch;
drop it from the forward-path parametrize (minimax-oauth/qwen-oauth remain).
MoA's _slot_runtime() whitelists providers that must keep their provider
identity (so call_llm runs their provider branch) instead of being treated
as a plain custom endpoint via forwarded base_url/api_key. Native anthropic
was missing from this set.
Native anthropic subscription OAuth setup-tokens (sk-ant-oat*) require Bearer
auth plus the 'anthropic-beta: oauth-*' header, which only the anthropic
provider branch adds. Without the whitelist entry, the slot's base_url/api_key
were forwarded and call_llm sent the OAuth token as x-api-key, which Anthropic
rejects with a bare 429 (rate_limit_error with no quota details). This made
anthropic references in MoA presets fail every time.
Add 'anthropic' to the whitelist so native anthropic reference/aggregator
slots route through the provider branch. Extends upstream 9229d0db1 which
added 'nous' for the same reason.
_resolve_task_provider_model() flattened any explicit base_url to
provider=custom. Correct for bare/custom endpoints, but wrong for
provider-backed routes (anthropic, qwen-oauth, minimax-oauth,
openai-codex, etc.) whose provider branch adds auth refresh, transport,
or request shaping. MoA reference slots resolved through those providers
lost their identity before the aux call, so e.g. a Codex reference hit
chatgpt.com/backend-api/codex without its Cloudflare headers and got
HTML back (surfacing as a spurious rate-limit).
Keep first-class providers intact when paired with a resolved base_url
via _preserve_provider_with_base_url(); bare/custom/auto/unknown and the
direct openai alias still route through custom.
Co-authored-by: Hermes Agent <127238744+teknium1@users.noreply.github.com>
The advisory reference view stripped all tool calls and tool results, so
reference models judged a task whose actions and results they never saw — and
references only fired once per user turn, never re-running as the agent's
state advanced through the tool loop.
Two fixes:
- _reference_messages() now PRESERVES the agent's tool calls and tool results,
rendering them inline as text ([called tool: ...] / [tool result: ...]) so a
reference gives an informed judgement on the real current state. Still emits
zero tool-role messages and zero tool_calls arrays (strict providers reject
those), and large tool results are previewed head+tail (4000-char budget).
The required end-on-user shape is met by APPENDING a synthetic advisory user
turn — not by deleting the agent's latest context (which the prior fix did).
- References now re-run on every state change — each new user message AND each
new tool result — instead of once per user turn. The state-sensitive advisory
signature drives the cache: new tool result = miss (re-run), identical-state
re-call = hit (no re-run, no re-emit).
The acting aggregator still receives the full, untrimmed transcript.
* fix(moa): reference advisory view must end with a user turn
MoA reference calls failed with Anthropic models that don't support
assistant prefill (e.g. Claude Opus 4.8): '400 ... must end with a user
message'. The advisory view built by _reference_messages() kept the last
assistant turn's text while dropping the following tool result, leaving a
trailing assistant turn — which Anthropic (and OpenRouter->Anthropic)
interpret as an assistant prefill to continue. References are advisory and
must end on the user turn they answer.
Strip trailing assistant turns from the advisory view (preserving
intervening ones). Update the existing test that encoded the buggy shape
and add a mid-tool-loop regression test.
* feat(moa): give reference models an advisory-role system prompt
Reference models received the bare trimmed conversation with no role
framing, so they assumed they were the acting agent and refused ("I can't
access repositories/URLs from here") or tried to call tools they don't have.
Prepend a dedicated advisory system prompt to every reference call: the
model is an analyst, not the actor — it cannot execute, should not
apologize for lacking tools, and should reason about the presented state to
advise the aggregator/orchestrator on approach, next steps, tool-use
strategy, risks, and anything the acting agent missed. Its output is private
guidance for the aggregator, not a user-facing answer.
When a MoA preset is selected, each reference model's answer now renders in the
CLI as a thinking-style block labelled with its source model, BEFORE the
aggregator responds — so the mixture-of-agents process is visible instead of a
silent pause. The aggregator's response (and its tool actions) follow as normal.
Mechanism (shared seam, all surfaces):
- MoAChatCompletions/MoAClient take an optional reference_callback and emit
'moa.reference' (index/count/label/text) per reference, then 'moa.aggregating'
(aggregator label) once. agent_init wires this to the agent's
tool_progress_callback, which every surface already consumes — so the events
reach CLI/TUI/desktop/gateway with no new plumbing.
- CLI _on_tool_progress renders 'moa.reference' as a labelled '┊ ◇ Reference
i/n — <model>' header + a thinking-style preview (reusing _emit_reasoning_
preview), and 'moa.aggregating' as a spinner transition. Display-only; never
touches message history (cache-safe).
Turn-scoped reference cache: the agent loop calls the facade once per tool-loop
iteration, but the advisory message view is identical across iterations within a
turn, so references are now run AND displayed once per user turn (keyed by the
advisory view's signature) instead of re-running/re-spamming on every iteration.
This also cuts reference API cost from O(iterations) back to O(turns).
Verified live via interactive PTY on the opus-gpt preset (gpt-5.5 + opus refs):
reference blocks render once per turn, labelled by model, before the aggregator;
fresh blocks on each new turn; aggregator tool actions still execute.
Follow-up: TUI/desktop rich rendering + gateway batched-summary already receive
the events via tool_progress_callback; their surface-specific renderers are a
separate change.
MoA was calling reference and aggregator models through a bare
call_llm(provider=slot["provider"], model=slot["model"]) with a forced
temperature and a forced max_tokens (the preset's hardcoded 4096). That left
base_url/api_key/api_mode unresolved — so the auxiliary auto-detector guessed
the API surface instead of using the provider's real runtime, and the 4096 cap
truncated long aggregator syntheses.
A MoA slot is just a model selection and must be called the same way any model
is called elsewhere. Each slot is now resolved through resolve_runtime_provider
(the canonical provider→api_mode/base_url/api_key resolver the CLI, gateway, and
delegate_task all use) via a new _slot_runtime() helper, and the resolved
endpoint is passed into call_llm. So a reference/aggregator gets its provider's
actual API surface — MiniMax → anthropic_messages, GPT-5/o-series →
max_completion_tokens, custom endpoints → their base_url — identical to how that
model is handled as the acting model.
MoA also no longer imposes its own output cap: max_tokens defaults to None
(omitted → the model's real maximum) for references and is passed through from
the caller for the aggregator. The preset's hardcoded 4096 is gone. The
max_tokens preset config field is left in place (config/web/desktop unchanged);
it is simply no longer applied as a forced cap.
Tests: slots route through resolve_runtime_provider with resolved base_url/
api_key; resolution errors fall back to bare provider/model; neither call
carries an output cap even when the preset config still contains max_tokens.
* feat(moa): expose MoA presets as selectable virtual models
Reconstructed onto current main (PR #46081's base had diverged with no common
ancestor, marking the PR dirty so CI never dispatched). MoA is now a virtual
provider: each named preset is a selectable model under provider 'moa', and the
preset's aggregator is the acting model that answers and calls tools.
Reference models fan out in parallel via a bounded ThreadPoolExecutor (the same
batch pattern delegate_task uses) — all references dispatched at once, collected
when every one finishes, then handed to the aggregator. Output order is
preserved, failures and the MoA-recursion guard stay isolated per reference.
- Removed the old mixture_of_agents model tool and moa toolset.
- Added moa as a virtual provider in the provider/model inventory.
- /moa is shortcut behavior over model selection (default preset / named preset
/ one-shot prompt).
- Dashboard + Desktop manage named presets; presets appear in model pickers.
- Parallel reference fan-out in agent/moa_loop.py with regression test.
* fix(moa): thread moa_config through _run_agent to _run_agent_inner
The reconstructed gateway MoA wiring declared moa_config on _run_agent (the
profile-scoping wrapper) and used it inside _run_agent_inner, but the wrapper
never forwarded it — _run_agent_inner had no such parameter, so the runtime hit
NameError: name 'moa_config' is not defined on the compression-failure session
sync path. Add moa_config to _run_agent_inner's signature and forward it from
both wrapper call sites (multiplex and non-multiplex). Caught by
tests/gateway/test_compression_failure_session_sync.py on CI shard test(4).
* fix(moa): classify moa as a virtual provider in the catalog
The moa virtual provider has no PROVIDER_REGISTRY/ProviderProfile entry, so
provider_catalog() fell through to the default auth_type="api_key" with no
env vars — tripping two catalog invariants:
- test_provider_catalog: api_key providers must expose a credential env var
- test_provider_parity: every hermes-model provider must be desktop-configurable
moa already declares auth_type="virtual" in HERMES_OVERLAYS; consult that
overlay as an auth_type fallback so the catalog reports moa as virtual (no real
credential, no network endpoint). Exempt virtual providers from the desktop
parity union check the same way 'custom' is exempt — derived from the catalog,
not a hardcoded slug, so future virtual providers are covered too.
