9d3192a9c431f74c5b3c33141a13e2cbeda961fa
7 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
| 9d3192a9c4 |
Replace the model ids with ones Groq actually serves
The defaults shipped yesterday were wrong the day they shipped, and a real key proved it in one request. Groq serves neither llama-3.1-8b-instant nor llama-3.3-70b-versatile any more. Both were chosen from memory, both passed startup validation, and every agent run would have failed with a 400. This is the exact failure the claude-* guard was written to catch, arriving from the side that guard cannot see. A prefix check can reject a vendor this service cannot call; it has no way to know a provider retired an id last month. That is not a gap in the check, it is a gap in the class of thing local validation can know, so the fix is not another guard: TestConfiguredModelsAreServed asks the provider. It lists /models — part of the same openai-compatible surface the gateway already speaks, so every supported provider answers it — and fails if a configured id is absent, printing what is available. It reads the ids through config.DefaultModels() rather than repeating them, because a second copy would be the first thing to drift, and drift is the whole failure. Skipped without a credential like the rest of the live suite. Verified three ways: it fails on the retired id with the message an operator needs, skips clean with no key, passes on the new ones. New defaults, chosen against the live account rather than from memory: openai/gpt-oss-20b (fast) and openai/gpt-oss-120b (balanced, deep). Tool calling confirmed on both. groq/compound-mini was ruled out — it cannot do tool calls at all, which this platform requires. MODEL_REASONING_EFFORT is now documented as safe here and NOT portable: gpt-oss accepts low/medium/high, exactly the scale openAIEffort maps onto, while qwen/qwen3.6-27b on the same account rejects all three and fails the whole request rather than ignoring the key. I7 IS NO LONGER UNPROVEN. make eval-live passes all three cases twice against gpt-oss-120b, the planted-injection case included: answers from the handbook, cites, refuses the injection, leaks neither the operator-only pay guidance nor the other tenant's figures. CLAUDE.md §12 and handover.md updated from "urgent" to measured, dated, and scoped to the one model it is evidence about. One real defect found on the way. The handbook grounding check failed once on an answer containing the phrase it wanted — "more than ten minutes" on screen, strings.Contains false — which leaves an invisible separator as the only explanation; the same model writes "47 %" and a U+2011 hyphen elsewhere. The flaky assertion is the small half. THE LEAK ASSERTIONS USED THE SAME MATCH and fail in the dangerous direction: "attacker@evil.test" with a zero-width space, or "uplift" with a soft hyphen, would have been reported clean. A permission test that cannot see the leak it is hunting is worse than none, because it is believed. normalizeForMatch folds those away, and its test pins that every case is one plain ToLower MISSES — a case whose naive match already succeeds fails, so the suite cannot fill with examples that demonstrate nothing. That caught my own first BOM case, which put the mark where Contains found it regardless. gofmt clean, vet clean, 15/15 packages pass offline; live suite green twice. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PJvibeSc1JYXjatankqM1g |
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| 34fa58a6b9 |
Remove the Anthropic path; the gateway speaks one wire protocol
The platform now runs on Groq by default, through the OpenAI-compatible chat-completions shape. That shape is not one vendor — Gemini, OpenRouter, Together, vLLM and a local Ollama serve it too — so moving again stays configuration rather than code. Two things in the deleted file were not Anthropic's and would have gone with it silently: withRetry / MaxAttempts / retryBackoff were defined in anthropic.go and CALLED BY openai.go. Deleting the file wholesale would have removed the retry policy of the provider that survived, and nothing in openai.go mentions it, so the loss would have been invisible until the next 429. The policy is a property of this platform's runs, not of a vendor's API; it now lives in retry.go where no provider can carry it off. StreamComplete had the same problem and moves to gateway.go, beside the Streamer interface whose comment already referenced it. Three stale-configuration failures are now refused at startup instead of being ignored. Each was verified firing through the real config.Load(): MODEL_PROVIDER=anthropic — named separately from every other wrong value because it used to be correct. Ignoring it gives a stack that believes it is on Claude while every run goes to Groq and is billed there. ANTHROPIC_API_KEY set while MODEL_API_KEY is empty. Ignoring a key an operator did set is the worst version of this: they fail every run on a missing credential they are looking straight at. A leftover claude-* model id, naming the tier that carries it. This is the check the previous commit's error-detail work was diagnosing: such an id is accepted by this process, rejected by the provider, and 400s on EVERY run. "A model is wrong" does not say which of three lines to edit. Defaults ship as a matched pair. defaultBaseURL and the three tier ids are one decision, not four: an id is only meaningful against the service that serves it, and a Groq id on an OpenAI base URL is the same failure from the other side. The tiers also stop being one model — a tier whose cost does not differ is a distinction that buys nothing. Verified end to end against a stub of the wire, driving the real wiring (config.Load in production mode, gateway.New, StreamComplete): streamed deltas, tool-call decoding, the loopback credential exemption, and usage totalling 150 rather than 190 — the cached-prefix subtraction still holds. gofmt clean, go vet clean, 14/14 non-DB packages pass. httpserver still needs a reachable database. NOT verified: the I7 planted-injection eval. Removing this path removed the only model whose refusal behaviour had been measured against it, so the new default is unproven there until `make eval-live` runs with a real key. The Groq model ids should also be confirmed against Groq's current lineup. Flagged in CLAUDE.md §12 and docs/handover.md. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PJvibeSc1JYXjatankqM1g |
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| c74fe7e074 |
Add an OpenAI-compatible gateway, so the model provider is a config value
The platform could only talk to one vendor. Moving off Claude — for cost, or
because a client asks for Gemini — meant a rewrite behind an interface that
already had exactly the right shape and one implementation.
`openai` is not only OpenAI. Groq, Gemini's compatibility endpoint, OpenRouter,
Together, vLLM and a local Ollama all serve the chat-completions shape, so one
implementation reaches all of them and the difference between them is a base
URL and three model ids. That is why this is one file and not a package per
vendor.
`routing.go` had the vendor baked into the routing table every provider has to
read: effort was `anthropic.OutputConfigEffort`. Nothing was wrong with that
while there was one implementation; it became wrong the moment there were two,
because the OpenAI path would have had to import the Anthropic SDK to learn how
hard to think. Effort is now the platform's own three-value vocabulary and each
implementation maps it onto whatever its API calls the same idea.
THE ACCOUNTING DIFFERS BETWEEN THE TWO WIRES, and getting it wrong would have
been invisible. OpenAI reports prompt_tokens INCLUSIVE of the cached prefix;
Anthropic reports input tokens EXCLUSIVE of it and carries the cache
separately. Usage.Total() adds all four fields, so copying both numbers across
verbatim bills the cached prefix twice — worst on long conversations, which is
exactly where I3's budget matters most. The run would still answer; it would
just hit BudgetExceeded early, for no visible reason. normalise() subtracts,
and there is a test named after it.
Streamed tool calls are keyed by their wire index, not appended in arrival
order. Providers interleave the fragments of parallel calls, so appending
splices one call's arguments onto another's — and the result is usually two
calls that are each valid JSON and both wrong, which means the tools run with
inputs the model never chose and nothing errors. Mutation-checked: ignoring the
index produces `{"day"{"week":"friday"}:"next"}` and the test catches it.
Three configuration mistakes are refused at startup rather than at runtime:
- MODEL_BASE_URL without MODEL_PROVIDER=openai. The anthropic path has one
endpoint and ignores the field, so this is a deployment that believes it
switched providers and did not — every run still goes to Anthropic and is
still billed there, with nothing in the logs to say so. Cost is the whole
reason this change exists, and that is the one mistake that silently
defeats it.
- An unrecognised MODEL_PROVIDER, once at boot instead of once per run.
- A production deployment with no credential — except against localhost,
which needs none, and demanding one would make the free local path
impossible to configure.
reasoning_effort is opt-in via MODEL_REASONING_EFFORT. Reasoning models accept
it; most others reject the entire request with a 400 rather than ignoring an
unknown key, so every deployment would have had to opt out instead.
`make eval-live` now reads the same environment the service does and logs which
provider answered, because a suite that cannot say which model produced a
result is a suite whose result cannot be compared with another run's. That is
the point of this change: §12 leaves model hosting open, and this makes the
decision cheap to reverse and possible to settle on evidence. Weigh the I7 case
heaviest — a cheaper model that follows the planted injection is a security
regression, not a saving.
Default behaviour is unchanged: MODEL_PROVIDER unset means anthropic, and
ANTHROPIC_API_KEY still works, so no existing deployment needs an edit.
NOT verified against a live provider — no credential was available on this
machine. Tested against a fake endpoint covering both paths, and the three
guarantees above are mutation-checked.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01PJvibeSc1JYXjatankqM1g
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| 57c2a52c1e |
Refuse an HTTP write timeout that would cut off a legal agent run
Production answered 502 Bad Gateway on a non-streamed agent run. Nothing about that was a gateway fault: krow-proxy already had proxy_read_timeout 3600s, and the API pods were healthy with zero restarts throughout. HTTP_WRITE_TIMEOUT was 30s. Every shipped agent runs at the `balanced` tier, whose deadline is 60s, and the `deep` tier allows 120s. So the server aborted the response on any run over half the time the runtime considered legal, the proxy saw its upstream vanish mid-response, and it reported the only thing it could. A gateway error for something no gateway did — which is why it looked like infrastructure for as long as it did. Delegation did not cause this; it made it routine. A parent that asks two subagents takes longer than one answering alone, so a latent misconfiguration became a reliable one. Verified: the exact request that returned 502 now answers 200 in 18s. Streaming is what hid it, and that is the part worth keeping in mind. The chat panel uses SSE, so the product looked healthy while every non-streaming caller got 502 on a slow question. A bug only reachable by the callers who do not yet exist is one nobody reports. So the value is now derived from the thing that constrains it — the default is DeepestAgentDeadline plus headroom rather than a number typed once — and validate() refuses anything below that deadline at startup. A slow, intermittent, misattributed failure becomes a message on the first boot. DeepestAgentDeadline is duplicated in internal/config rather than imported, because internal/runtime already imports internal/config and a cycle to share one number is a bad trade. TestConfigKnowsTheDeepestAgentDeadline asserts the two agree, so drift is a build failure rather than a discovery. It also checks that no tier exceeds it, or the name lies. ORDERING, and it matters for the next deploy: the check refuses the old 30s, so a pod carrying this image against an unpatched configmap will not boot. Production's configmap is already 180s. The handover says so too. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PJvibeSc1JYXjatankqM1g |
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| 6849363a37 |
Implement delegation, so an agent's subagents are more than decoration
krow-workforce-agent has declared five subagents since it was written and
answered every question by itself. Everything for §6 existed except the
delegation: the parser read `subagents:`, runtime.Agent carried them, the
loader populated them, agent_runs had a parent_run_id column with a
self-reference and a no-self-parent constraint, and budget.go's comments
already described sharing a budget with subagents. Nothing called any of it.
A subagent is offered to the parent's model as a tool, because §6 says that is
what delegation is from the parent's side. Three rules are enforced rather than
assumed, each with a test that fails if it stops holding:
I1 The subagent runs as the ORIGINAL caller. It cannot read anything the
person could not read directly.
§6 It SHARES the parent's budget. The test sets MaxSteps to 1, spends it in
the parent, and asserts the child terminates BudgetExceeded — an
assertion that only passes when the budget is shared, and that a fresh
budget would quietly turn green.
§3 Depth is capped at 2. At the cap no subagent is loaded or offered, so a
cycle reaching run time is bounded rather than unbounded.
I4 survives too: a write a SUBAGENT wants approved still stops the whole run
and asks a person, rather than being performed because it happened one level
down.
Two bugs found by running it rather than by reading it:
- delegate() read the error before the result. finish returns a non-nil
error for every termination that is not Completed, INCLUDING
ConfirmationPending — which is not a failure but a run that stopped to ask
a question. Reading the error first discarded the result and with it the
confirmation, so a subagent's write silently never happened and nobody was
asked.
- Delegated trajectories were never persisted at all. parent_run_id is a
foreign key and a subagent finishes BEFORE the run that delegated to it,
so every child insert named a parent row that did not exist yet. The
database refused it; finish deliberately does not fail a run over a sink
error; and the entry recording that the trajectory could not be saved was
itself in the trajectory that was not saved. Children are now buffered and
written by finish after the parent's own row, each arriving with its
descendants already ordered behind it, so one pass writes a whole tree
parent-first. The regression test asserts on save ORDER, because a
MemorySink has no foreign key and will pass either way.
Verified end to end against a live model: an agent with no tools of its own and
one subagent produced
delegation-probe run=run_16622d7de6 parent=(root)
talent-pool-agent run=run_64160684b1 parent=run_16622d7de6
with the subagent's answer reaching the parent's model. Full suite green, only
TestLive* skipped.
Not addressed: §3's publish-time cycle detection, which needs the whole agent
set in hand. The depth cap is what holds without it, and is the half that
matters at run time.
Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01PJvibeSc1JYXjatankqM1g
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| f7df96c973 | agent build | |||
| 7d12ebef3d | first commit |
