Recommendation
Fix the Smoke Gemini engine model — it is set to a non-agent TTS preview (gemini-3.1-flash-tts-preview) that the AWF api-proxy has no pricing for, so every inference call is rejected and the smoke canary is 100% red.
Problem statement
Smoke Gemini fails at "Execute Gemini CLI" with ApiError type unknown_model_ai_credits: model gemini-3.1-flash-tts-preview has no AI-credits pricing and no default pricing configured in the api-proxy (apiProxy.defaultAiCreditsPricing unset / model absent from the pricing table). The proxy rejects every generateContent / generateContentStream call, so 0 agent turns run and the agent job fails.
Affected workflow and run IDs
- Workflow:
.github/workflows/smoke-gemini.lock.yml (Gemini engine)
- Run IDs: §27480363197, §27478319753 — identical signature, 100% failure this window.
Evidence
- Both
GeminiChat.sendMessageStream (Turn.run) and BaseLlmClient.generateJson (classifier route) throw the same ApiError after retryWithBackoff exhausts retries.
token_usage.jsonl is 0 bytes; agentic_fraction = 0 — no model call ever completed.
- Two
gemini-client-error artifacts per run with byte-identical payloads.
- (Incidental, non-causal: 94% firewall block rate; the proxy-allowed inference endpoint itself returned the pricing error.)
Probable root cause
gemini-3.1-flash-tts-preview is a text-to-speech preview model, not an agent chat model, and is unknown to the proxy's AI-credits pricing table. This is a misconfigured/unintended model selection for an agent smoke test.
Proposed remediation
- Point Smoke Gemini at a supported Gemini agent model (the model the canary is meant to validate), not a TTS-preview SKU.
- Add the model (or a
defaultAiCreditsPricing fallback) to the api-proxy pricing table so an unknown model degrades to a clear pricing error earlier, not deep in retry exhaustion.
Success criteria / verification
- Smoke Gemini "Execute Gemini CLI" completes with ≥1 successful agent turn; no
unknown_model_ai_credits error over a 24h window.
Context
Filed by [aw] Failure Investigator (6h) — analyzed run https://github.com/github/gh-aw/actions/runs/27484878458. Parent: Workflow Health Manager Issue Group #29109.
Related to #29109
Related to #29109
Generated by 🔍 [aw] Failure Investigator (6h) · 421.4 AIC · ⌖ 12.8 AIC · ⊞ 4.5K · ◷
Recommendation
Fix the Smoke Gemini engine model — it is set to a non-agent TTS preview (
gemini-3.1-flash-tts-preview) that the AWF api-proxy has no pricing for, so every inference call is rejected and the smoke canary is 100% red.Problem statement
Smoke Gemini fails at "Execute Gemini CLI" with
ApiErrortypeunknown_model_ai_credits: modelgemini-3.1-flash-tts-previewhas no AI-credits pricing and no default pricing configured in the api-proxy (apiProxy.defaultAiCreditsPricingunset / model absent from the pricing table). The proxy rejects everygenerateContent/generateContentStreamcall, so 0 agent turns run and the agent job fails.Affected workflow and run IDs
.github/workflows/smoke-gemini.lock.yml(Gemini engine)Evidence
GeminiChat.sendMessageStream(Turn.run) andBaseLlmClient.generateJson(classifier route) throw the sameApiErrorafterretryWithBackoffexhausts retries.token_usage.jsonlis 0 bytes;agentic_fraction = 0— no model call ever completed.gemini-client-errorartifacts per run with byte-identical payloads.Probable root cause
gemini-3.1-flash-tts-previewis a text-to-speech preview model, not an agent chat model, and is unknown to the proxy's AI-credits pricing table. This is a misconfigured/unintended model selection for an agent smoke test.Proposed remediation
defaultAiCreditsPricingfallback) to the api-proxy pricing table so an unknown model degrades to a clear pricing error earlier, not deep in retry exhaustion.Success criteria / verification
unknown_model_ai_creditserror over a 24h window.Context
Filed by [aw] Failure Investigator (6h) — analyzed run https://github.com/github/gh-aw/actions/runs/27484878458. Parent: Workflow Health Manager Issue Group #29109.
Related to #29109
Related to #29109